numerical modelling of sinusoidal brushless motor for … · 2017-05-12 · modelling of the pmsm...
TRANSCRIPT
Abstract:
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failure
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
Key
1In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
brushes.
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
condition
multi
development of simulation algorithms properly
sensitive to faults.
Abstract:
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failure
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
Key
1 IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
brushes.
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
condition
multi
development of simulation algorithms properly
sensitive to faults.
Abstract:
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failure
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
Key-Words:
IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
brushes.
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
condition
multi-domain numerical method which allows the
development of simulation algorithms properly
sensitive to faults.
Abstract:
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failure
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
Words:
IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
brushes. This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
conditions. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
sensitive to faults.
Abstract: - The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failure
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
Words: -
IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
sensitive to faults.
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
identify failures. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
- PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
sensitive to faults.
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
IntroductionIn the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
sensitive to faults.
Numerical Modelling of Sinusoidal Brushless
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
Introduction In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
first reported during high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
brush wear occurred [1-
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to ov
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
-3]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
have been designed to overcome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
research activity focused on the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM mode
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
ITALY
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
prognostic applications. For this purpose, short-
circuit and static eccentricity failure conditions will
be implemented in the developed PMSM model.
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
ITALY
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
In the last few years, the interest in brushless motors
has increased because of their advantages compared
with traditional brushed motors. The need of
improvement in the design of electric motors was
high altitude strategic bombing
in World War II: in fact, at about 30000 ft, a rapid
]. Later on, during space
exploration, the brush problem became crucial due
to the outgassing phenomena. Brushless motors
ercome the brushed motor
disadvantages: the electronic commutation, which is
made possible by using electronic switches, replaces
the mechanical commutation based on carbon made
This study shows the firs results of our
the numerical
modelling of the PMSM for electromagnetic
aerospace actuator systems for future diagnostic and
-
circuit and static eccentricity failure conditions will
l.
Furthermore, the developed model takes into
account dry friction and it overcomes the typical
limitations (e.g. simplifying assumptions such as the
superposition of the effects) which are unable to
assess nonlinear effects arising from failure
s. This purpose is achieved by means of a
domain numerical method which allows the
development of simulation algorithms properly
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
ITALY
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the si
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24
ITALY
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
of the multi domain simulation is necessary to improve the simplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
2 Flight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
decades, fl
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
by systems)
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
Corso Duca degli Abruzzi 24 –
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
decades, fl
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
by systems)
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Fig. 1:
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
Politecnico di Torino
– 10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
increased acceptance as they are becoming more and more safety-critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
decades, fl
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
by systems)
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Fig. 1:
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
decades, fl
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
by systems)
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Fig. 1: Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
decades, flight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
by systems).
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
Indeed, w
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
Indeed, w
systems, EMAs off
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
10129, Turin
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical act
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
Indeed, w
systems, EMAs offer many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
next generation aircraft, based on the More Electric design. Electromechanical actuators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
Indeed, with respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
Motor for Aerospace Actuator Systems
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
Department of Mechanical and Aerospace Engineering
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
Numerical Modelling of Sinusoidal Brushless
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
[email protected], [email protected]
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quic
several fields of aerospace technology.
Schematic of the considered EMA system
M. D. L. DALLA VEDOVA P. MAGGIORE M. SCANAVINO
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to con
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
systems based on EMAs is quickly increasing in
several fields of aerospace technology.
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
PMSM, Electromechanical Actuator (EMA), Prognostics, PHM, Numerical Model
EM Flight Control ActuatorsFlight control systems allow to control the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes
ight control actuators were generally
hydromechanical or electrohydraulic but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
kly increasing in
several fields of aerospace technology.
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
in numerical models and that are mostly used for prognostic analyses of electromechanical actuators.
EM Flight Control Actuatorstrol the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
around one of the three body axes; in the last
ight control actuators were generally
but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated.
reasons, as reported in [4], the use of actuation
kly increasing in
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
EM Flight Control Actuators trol the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
in the last
ight control actuators were generally
but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
flammable or polluting, can be eliminated. For these
reasons, as reported in [4], the use of actuation
kly increasing in
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
trol the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
in the last
ight control actuators were generally
but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
For these
reasons, as reported in [4], the use of actuation
kly increasing in
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
trol the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
in the last
ight control actuators were generally
but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
For these
reasons, as reported in [4], the use of actuation
kly increasing in
Schematic of the considered EMA system
The interest in electromechanical actuators (EMA) has been growing because of the development of
uators have been gaining
critical actuation devices: for prognostics and
health management purposes of EMA, reliable and representative simulation models are needed in order to
s. This paper presents a multi domain model of EMA and it focuses on the numerical modelling
of the Permanent Magnet Synchronous Motor (PMSM), also kwon as Sinusoidal Brushless Motor. The choice
mplifying hypotheses that are typically considered
trol the aircraft
dynamic: this is made possible by means of the
proper actuation of the flight control surfaces.
The aerodynamic forces, exerted on the flight
control surfaces, will result in the aircraft rotation
in the last
ight control actuators were generally
but, especially
in recent years, the electromechanical systems are
gradually asserting (e.g. UAVs, secondary or stand-
ith respect to hydraulic
er many advantages: overall
weight is reduced, maintenance is simplified and
hydraulic fluids, which are often contaminant,
For these
reasons, as reported in [4], the use of actuation
kly increasing in
WSEAS TRANSACTIONS on POWER SYSTEMS M. D. L. Dalla Vedova, P. Maggiore, M. Scanavino
E-ISSN: 2224-350X 102 Volume 12, 2017
for primary flight control, is presented. The EMA
system is composed by:
1.
2.
3.
4.
5.
6.
3The authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
composed by five subsystems:
1.
2.
3.
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
1. an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
current (
2. a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
3. an electric motor, often a
type
4. a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
5. a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
6. a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
3 Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
1. W_ref
motor speed;
2. PMSM Motor Controller Model
actuator control electronics closing
loops and generat
3. PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
current (
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
type
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
W_ref
motor speed;
PMSM Motor Controller Model
actuator control electronics closing
loops and generat
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
current (
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
type;
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
W_ref: input block that generates the reference
motor speed;
PMSM Motor Controller Model
actuator control electronics closing
loops and generat
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
current (I_ref
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
W_ref: input block that generates the reference
motor speed;
PMSM Motor Controller Model
actuator control electronics closing
loops and generat
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
I_ref
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
motor speed;
PMSM Motor Controller Model
actuator control electronics closing
loops and generat
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
I_ref);
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
motor speed;
PMSM Motor Controller Model
actuator control electronics closing
loops and generat
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
PMSM Motor Controller Model
actuator control electronics closing
loops and generating
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
system is composed by:
an actuator control elect
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
the electrical power
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
current controller, pulse-
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
PMSM Motor Controller Model
actuator control electronics closing
ing the reference current
PMSM Motor ElectroM
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
an actuator control electronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
system to the electric motor;
an electric motor, often a
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
-wi
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
PMSM Motor Controller Model
actuator control electronics closing
the reference current
PMSM Motor ElectroMecc. Model
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
generated by the three-phase electrical
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
system to the electric motor;
an electric motor, often a three
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
width modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
sensors and considered faults).
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
composed by five subsystems:
: input block that generates the reference
PMSM Motor Controller Model
actuator control electronics closing
the reference current
PMSM Motor ElectroMecc. Model
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
phase electrical
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
system to the electric motor;
three
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
efficiency can be performed;
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
(reported in Fig.1 as RVDT).
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
PMSM Motor Controller Model
actuator control electronics closing
the reference current
ecc. Model
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
phase electrical
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
three-phase
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
feedback loops (current, motor spee
position) controlling the whole actuation system
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
PMSM Motor Controller Model: it simulates th
actuator control electronics closing
the reference current
ecc. Model
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
phase electrical
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
phase
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
feedback loops (current, motor speed and angular
position) controlling the whole actuation system
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
: it simulates th
actuator control electronics closing the feedback
the reference current
ecc. Model: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
phase electrical
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
phase
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
d and angular
position) controlling the whole actuation system
Proposed PMSM Numerical MThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
: it simulates th
the feedback
the reference current
: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
phase electrical regulator;
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
phase brushless
a gear reducer that decreases the motor angular
speed and increases its mechanical torque;
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
d and angular
position) controlling the whole actuation system
Proposed PMSM Numerical ModelThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
: it simulates th
the feedback
the reference current I_ref
: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
regulator;
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
brushless
a gear reducer that decreases the motor angular
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
d and angular
position) controlling the whole actuation system
odelThe authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
: it simulates th
the feedback
I_ref
: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
regulator;
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
brushless
a gear reducer that decreases the motor angular
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
d and angular
position) controlling the whole actuation system
odel The authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
Fig. 2: Block diagram of the EMA numerical model
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
: it simulates the
the feedback
I_ref;
: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
regulator;
In Fig. 1, an electromechanical actuator scheme,
for primary flight control, is presented. The EMA
ronics (ACE) that closes
the feedback loop, by comparing the commanded
position (FBW) with the actual one; it elaborates
the corrective actions and generates the reference
a Power Drive Electronics (PDE) that regulates
from the aircraft electrical
brushless
a gear reducer that decreases the motor angular
a system that transforms rotary motion into linear
motion: ball screws or roller screws are usually
preferred because a conversion with higher
a network of sensors that are used to close the
d and angular
position) controlling the whole actuation system
The authors’ models implement the motor features
only (rotor speed control loop and related reference
dth modulation (PWM)
inverter, electromagnetic model of the stator circuit
and related electromechanical model, internal
The proposed model is shown in Fig. 2 and it is
: input block that generates the reference
e
the feedback
: it simulates
the power drive electronics and the sinusoidal
PMSM electromagnetic behaviour. Furthermore,
it evaluates the mechanical torque developed by
the electrical motor as a function of the voltages
4.
5.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
switches [5].
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
resistance
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative.
is
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Three different reference systems are introduced to
study the PMSM (
1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
degree
TR
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
switches [5].
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Phase
Phase
Back
Each phase line is characterised by the same
resistance
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative.
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Three different reference systems are introduced to
study the PMSM (
where the
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
degree
TR: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
switches [5].
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Nominal voltage
Phase
Phase-
Torque constant
Back
Stall Torque
Rotor Inertia
Each phase line is characterised by the same
resistance
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative.
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Three different reference systems are introduced to
study the PMSM (
where the
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
degree-of
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
switches [5].
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Nominal voltage
Phase-phase resistance
-phase inductance
Torque constant
Back-EMF constant
Stall Torque
Rotor Inertia
Each phase line is characterised by the same
resistance R
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative.
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Fig. 4:
Three different reference systems are introduced to
study the PMSM (
axes
where the
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
of-freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
switches [5]. The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
Nominal voltage
phase resistance
phase inductance
Torque constant
EMF constant
Stall Torque
Rotor Inertia
Each phase line is characterised by the same
R and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative.
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Fig. 4:
Three different reference systems are introduced to
study the PMSM (
axes
where the
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
Nominal voltage
phase resistance
phase inductance
Torque constant
EMF constant
Stall Torque
Rotor Inertia
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
time derivative. The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Fig. 4: Brushless Reference systems
Three different reference systems are introduced to
study the PMSM (
axes: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
Nominal voltage
phase resistance
phase inductance
Torque constant
EMF constant
Stall Torque
Rotor Inertia
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
study the PMSM (as shown in
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
Nominal voltage
phase resistance
phase inductance
Torque constant
EMF constant
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
as shown in
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
axis of the phase 1.
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
phase resistance
phase inductance
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
as shown in
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
acting on the rotor shaft.
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
as shown in
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
PMSM Motor Dynamic Model
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
48
1.10
0.72
0.094
0.0544
0.34
0.047
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
as shown in Fig. 4)
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
PMSM Motor Dynamic Model: it simulates the
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
48
1.10
0.72
0.094
0.0544
0.34
0.047
Each phase line is characterised by the same
and the same inductance
the back electromagnetic force
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
Fig. 4)
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
Table 1: Main PMSM data
0.0544
Each phase line is characterised by the same
and the same inductance L
,
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
Fig. 4):
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
freedom dynamic system;
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Mo
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
[Nm/A
[V
[kg cm
Each phase line is characterised by the same
Leq; moreover,
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
brushless motor BLDC [6]. A Circuital Model with
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
[V]
[Ω
[mH]
[Nm/A
[Vpp
[Nm]
[kg cm
Each phase line is characterised by the same
; moreover,
and
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Brushless Reference systems
Three different reference systems are introduced to
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
del with
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
sinusoidal brushless motor (as reported in Table
[V]
[Ω]
[mH]
[Nm/App
pp/App
[Nm]
[kg cm2
Each phase line is characterised by the same
; moreover,
and
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
the back electromagnetic forces and currents.
Three different reference systems are introduced to
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
: input block that simulates the external load
It must be noted that these numerical models ca
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
del with
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
1).
pp]
pp]
2]
Each phase line is characterised by the same
; moreover,
are
introduced: they are related to the magnetic flux
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
Three different reference systems are introduced to
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
: it simulates the
motor mechanical behaviour by means of a two
: input block that simulates the external load
It must be noted that these numerical models can
also consider the electrical noise acting on the signal
lines [4], the rotor bearings dry friction and the limit
The PMSM model is the development
of the previous work carried out for the trapezoidal
del with
Detailed Inverter (CMDI) has been implemented:
the physical data used to implement these numerical
algorithms and to run the corresponding simulations
are referred to the TC 40 0.32 01 Tetra Compact
1).
Each phase line is characterised by the same
; moreover,
are
The layout of the numerical model
similar to the BLDC model shown in [6] but, in
this case, sinusoidal functions are used to describe
Three different reference systems are introduced to
: it is a stationary reference system
axis is fixed on the PMSM stator
and it is defined by starting from the symmetrical
WSEAS TRANSACTIONS on POWER SYSTEMS M. D. L. Dalla Vedova, P. Maggiore, M. Scanavino
E-ISSN: 2224-350X 103 Volume 12, 2017
2.
3.
The relative angle between the stator and the rotor
axes is
results
balance and, referred to
where
magnetic flux respectively.
The
right handed Cartesian system is obtained. The
angle
angles along the stator starting from the
2. the rotor. The
while the
The angle
angles along the rotor, starting from the
3. Three
reference system where the axes (1, 2 and
into line with the thr
motor:
1
The relative angle between the stator and the rotor
axes is
results
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
where
magnetic flux respectively.
The
right handed Cartesian system is obtained. The
angle
angles along the stator starting from the
the rotor. The
while the
The angle
angles along the rotor, starting from the
Three
reference system where the axes (1, 2 and
into line with the thr
motor:
1-axis corresponds to the
The relative angle between the stator and the rotor
axes is
results
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
where
magnetic flux respectively.
The
right handed Cartesian system is obtained. The
angle Φ
angles along the stator starting from the
the rotor. The
while the
The angle
angles along the rotor, starting from the
Three-phase reference system
reference system where the axes (1, 2 and
into line with the thr
motor:
axis corresponds to the
The relative angle between the stator and the rotor
axes is .
results that:
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
where P and
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
angle Φ is used as a polar coordinate to describe
angles along the stator starting from the
axes
the rotor. The
while the
The angle
angles along the rotor, starting from the
-phase reference system
reference system where the axes (1, 2 and
into line with the thr
motor: the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
. Applying Kirchhoff’s law on each line it
that:
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
and
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
Φ is used as a polar coordinate to describe
angles along the stator starting from the
axes: it is a rotating reference system with
the rotor. The
while the
The angle ξ is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
into line with the thr
the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three
0
The motor torque is obtained from the power
balance and, referred to
and λmagnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
the rotor. The
axis is perpendicular to the
The angle ξ is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
into line with the thr
the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three
0
The motor torque is obtained from the power
balance and, referred to
are the pole pair number and the
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
ξ is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
into line with the thr
the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
!
"
#
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
are the pole pair number and the
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
into line with the thr
the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three
The motor torque is obtained from the power
balance and, referred to
are the pole pair number and the
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
into line with the three
the axes are out of phase by 120° and the
axis corresponds to the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three
The motor torque is obtained from the power
are the pole pair number and the
magnetic flux respectively.
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate
angles along the rotor, starting from the
phase reference system
reference system where the axes (1, 2 and
ee-phase windings of the
the axes are out of phase by 120° and the
axis corresponds to the axis.
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate
angles along the rotor, starting from the
phase reference system: it is a stationary
reference system where the axes (1, 2 and
phase windings of the
the axes are out of phase by 120° and the
axis.
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
Moreover, for a balanced three-
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis is perpendicular to
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate
angles along the rotor, starting from the
: it is a stationary
reference system where the axes (1, 2 and
phase windings of the
the axes are out of phase by 120° and the
axis.
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
-phase circuit:
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the nor
axis is perpendicular to the
is a polar coordinate describing
angles along the rotor, starting from the
: it is a stationary
reference system where the axes (1, 2 and
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
phase circuit:
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the
: it is a rotating reference system with
axis points to the north pole line,
axis is perpendicular to the
describing
angles along the rotor, starting from the
: it is a stationary
reference system where the axes (1, 2 and
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
phase circuit:
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
angles along the stator starting from the axis;
: it is a rotating reference system with
th pole line,
axis is perpendicular to the
describing
angles along the rotor, starting from the axis;
: it is a stationary
reference system where the axes (1, 2 and
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
phase circuit:
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
axis;
: it is a rotating reference system with
th pole line,
axis.
describing
axis;
: it is a stationary
reference system where the axes (1, 2 and 3) fall
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
phase circuit:
The motor torque is obtained from the power
axes, it results [7]:
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
axis;
: it is a rotating reference system with
th pole line,
axis.
the
axis;
: it is a stationary
3) fall
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
(1)
(2)
(3)
(4)
The motor torque is obtained from the power
(5)
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
axis so that a
right handed Cartesian system is obtained. The
is used as a polar coordinate to describe
: it is a rotating reference system with
th pole line,
axis.
the
: it is a stationary
3) fall
phase windings of the
the axes are out of phase by 120° and the
The relative angle between the stator and the rotor
Applying Kirchhoff’s law on each line it
(1)
(2)
(3)
(4)
The motor torque is obtained from the power
(5)
are the pole pair number and the
Fig. 5: PMSM Electromechanical Model subsystem
Fig. 5: PMSM Electromechanical Model subsystem
phase reference currents from the reference
current, Park and Clarke transformations are needed
(as
obtained from the
motor torque is turned into the reference current by
using the motor torque
3.1The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
I_ref
speed and position. The reference current subsystem
generates the reference si
three
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation
the
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
failu
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
(as described
obtained from the
motor torque is turned into the reference current by
using the motor torque
3.1 The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
I_ref, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
three-
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation
the corresponding
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
failure as shown in [
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
described
obtained from the
motor torque is turned into the reference current by
using the motor torque
PMSMThe subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
-phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation
corresponding
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
re as shown in [
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
described
obtained from the
motor torque is turned into the reference current by
using the motor torque
PMSMThe subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation
corresponding
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
re as shown in [
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
described in
obtained from the
motor torque is turned into the reference current by
using the motor torque
PMSMThe subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation
corresponding
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
re as shown in [
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
in [8]
obtained from the
motor torque is turned into the reference current by
using the motor torque
PMSM Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
transformation matrixes are implemented to obtain
corresponding
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
re as shown in [
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
[8]).
obtained from the
motor torque is turned into the reference current by
using the motor torque
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
corresponding three
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The
implements the short circuit and static eccentricity
re as shown in [9
Fig. 5: PMSM Electromechanical Model subsystem
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
). The reference current (
obtained from the motor controller: a reference
motor torque is turned into the reference current by
using the motor torque
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
hree-
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
angular speed. The Failure Functions
implements the short circuit and static eccentricity
9].
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference si
phase circuit: the
are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
-phas
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
generates the reference sinusoidal currents for a
and
are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
phase reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
and are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
implemented in the Circuital Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
are set equal to the reference current
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
are set equal to the reference current I_ref
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
I_ref
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
Failure Functions
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
The reference current (I_ref
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
I_ref and zero
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
subsystem
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
I_ref
otor controller: a reference
motor torque is turned into the reference current by
Electromechanical Model The subsystem in Fig. 5 models a three-phase
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
and zero
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forc
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
subsystem
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three
phase reference currents from the reference
current, Park and Clarke transformations are needed
I_ref) is
otor controller: a reference
motor torque is turned into the reference current by
phase
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
and zero
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
e reference currents.
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
notice the normalized back electromagnetic forces,
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
subsystem
implements the short circuit and static eccentricity
It must be noted that, in order to obtain the three-
current, Park and Clarke transformations are needed
) is
otor controller: a reference
motor torque is turned into the reference current by
phase
circuit: it receives, as input, the reference current
, the electrical angle and the rotor mechanical
speed and position. The reference current subsystem
nusoidal currents for a
reference currents
and zero
respectively. The inverse Park and Clarke
matrixes are implemented to obtain
The PWM, Inverter, Phase Currents and Motor
Torque subsystems are the same as in [6],
Model with Detailed
Inverter model. On the left bottom of Fig. 5 we can
es,
which are sinusoidal functions of the electric angle.
The back electromagnetic forces are obtained
multiplying the normalized BEMFs and the motor
subsystem
implements the short circuit and static eccentricity
WSEAS TRANSACTIONS on POWER SYSTEMS M. D. L. Dalla Vedova, P. Maggiore, M. Scanavino
E-ISSN: 2224-350X 104 Volume 12, 2017
3.2
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
filter is a
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
PI
4In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
conditions.
nominal motor speed (3000 rpm). An external load
(50% of
%
history, while in Fig. 8 the BEMFs and the actual
three
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
3.2 The motor control is achieved by means of a PID
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
filter is a
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
PID PMSM speed controller are shown in Table 2.
&
4 ResultsIn this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
conditions.
nominal motor speed (3000 rpm). An external load
(50% of
%
history, while in Fig. 8 the BEMFs and the actual
three
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
filter is a
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
&' [Nm/rad/s]
0
ResultsIn this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
conditions.
nominal motor speed (3000 rpm). An external load
(50% of
0.15
history, while in Fig. 8 the BEMFs and the actual
three-phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
filter is added to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad/s]
0.025
ResultsIn this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
conditions.
nominal motor speed (3000 rpm). An external load
(50% of
15+
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad/s]
025
ResultsIn this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
conditions. The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
+.
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
speed controller
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad/s]
Results In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
speed controller [10]
to define the reference torque, which is turned into
the reference current
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at t
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
[10]: the input speed error is used
to define the reference torque, which is turned into
the reference current I_ref
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
&
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
load is applied; at the same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
I_ref
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad]
0.235
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
I_ref. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad]
235
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history
Fig. 7: PMSM motor speed time history
PMSM Speed ControllerThe motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad]
235
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
The motor torque time history is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
PMSM Speed Controller The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
&
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
& [Nm/rad/s
1
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad/s
1
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the
D PMSM speed controller are shown in Table 2.
Table 2: PMSM speed controller PID gains
[Nm/rad/s
6
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
Fig. 7: PMSM motor speed time history
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
ensure the stability of the entire system: a low-pass
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
maximum value allowed. The three gains of the said
D PMSM speed controller are shown in Table 2.
[Nm/rad/s2]
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
pass-
dded to the derivative line for this purpose.
The integral contribution is achieved with the anti-
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
said
D PMSM speed controller are shown in Table 2.
]
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
is shown in Fig. 10.
The motor control is achieved by means of a PID
: the input speed error is used
to define the reference torque, which is turned into
. The derivative term acts
on the signal error, properly filtered, in order to
-
dded to the derivative line for this purpose.
-
windup filter, which allows the desaturation of the
integral term when the reference torque reaches the
said
In this section, in order to explain the performance
of the proposed numerical model, the motor
response to a reference speed is presented, in load
The reference speed is set equal to the
nominal motor speed (3000 rpm). An external load
the stall torque) is applied at time
Fig. 7 shows the motor speed time
history, while in Fig. 8 the BEMFs and the actual
phase currents are shown. It can be noticed
that the phase currents increase when the external
he same time, a reduction in the
BEMFs is visible, due to the proportional
relationship between the motor speed and BEMFs.
In Fig. 9 the sinusoidal waveform of the actual three
phase currents and the reference ones are shown.
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque f
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque f
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque f
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque f
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque f
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque T
friction torque fatt time history
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
Fig. 10: PMSM motor torque TM
time history
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
M, external load T
time history
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
, external load T
time history
Fig. 8: BEMFs and phase currents
Fig. 9: PMSM reference and actual phase currents
, external load T
time history
Fig. 9: PMSM reference and actual phase currents
, external load T
Fig. 9: PMSM reference and actual phase currents
, external load TR
Fig. 9: PMSM reference and actual phase currents
R and
and
WSEAS TRANSACTIONS on POWER SYSTEMS M. D. L. Dalla Vedova, P. Maggiore, M. Scanavino
E-ISSN: 2224-350X 105 Volume 12, 2017
5 Conclusions The numerical modelling of the electromechanical
actuator using permanent magnet synchronous
motor has been developed. The model was created
in Matlab/Simulink environment. The Park and the
Clarke transformations were introduced to describe
the three-phase reference currents. The sinusoidal
waveform of the normalized back electromagnetic
force was introduced in order to describe the correct
motor behaviour and evaluate the total motor torque.
The PMSM motor control was developed imposing
the reference quadrature current and setting the
direct current equal to zero, as it normally does
not contribute to the motor torque generation.
In order to improve the developed model, some
suggestions are given:
1. the Hysteresis Control should be replaced with
the d-q axes direct control, in order to avoid the
phase voltage and current distortions at high
rotor speed;
2. the failure conditions could be studied in details.
Demagnetisation failure could be considered in
order to improve the failure conditions;
3. a simplified model of the actuator should be
developed in order to monitor the motor actual
behaviour. This solution would be interesting for
future diagnostic and prognostic applications.
References:
[1] Midwest Research Institute – NASA, Brushless
DC Motors, January 1975.
[2] NASA Practice No. PD-ED-1229, Selection of
electric motors for aerospace applications.
[3] P. Pillay, R. Krishnan, Application Charac-
teristics of Permanent Magnet Synchronous and
Brushless dc Motors for Servo Drives, IEEE
Transactions on industry applications, Vol.21,
No.5, September/October 1991.
[4] D. Belmonte, M. D. L. Dalla Vedova, P.
Maggiore, New prognostic method based on
spectral analysis techniques dealing with motor
static eccentricity for aerospace electro-
mechanical actuators, WSEAS Transactions On
Systems, Vol.14, 2015, ISSN: 1109-2777.
[5] L. Borello, M. D. L. Dalla Vedova, G. Jacazio,
M. Sorli, A Prognostic Model for Electro-
hydraulic Servovalves, Annual Conference of
the Prognostics and Health Management
Society, San Diego, CA, USA, 2009.
[6] L. Pace, M. D. L. Dalla Vedova, P. Maggiore,
S. Facciotto, Numerical methods for the
electromagnetic modelling of actuators for
primary and secondary flight controls,
Computational Science and Systems
Engineering, Vol.58, pp. 126-133, 2016. ISSN:
1790-5117
[7] P. Moreton, Industrial Brushless Servomotors,
Newnes, January 2000.
[8] S. Chattopadhyay, M. Mitra, S.Sengupta,
Electric Power Quality, Springer, Cap. 12.
[9] M. D. L. Dalla Vedova, P. Maggiore, L. Pace,
A. Desando, Evaluation of the correlation
coefficient as a prognostic indicator for
electromechanical servomechanism failures,
International Journal of Prognostics and
Health Management, Vol.6, No.1, 2015. ISSN:
2153-2648.
[10] M. H. Rashid, Power electronics handbook, 3rd
Edition, Butterworth-Heinemann, 2011.
WSEAS TRANSACTIONS on POWER SYSTEMS M. D. L. Dalla Vedova, P. Maggiore, M. Scanavino
E-ISSN: 2224-350X 106 Volume 12, 2017