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1. SPEED SENSORLESS CONTROL OF INDUCTION

MOTOR

Abstract This paper presents a novel speed sensorless vector control for induction motor. Indirect

field orientation concept is used to realize speed

and flux controllers. Speed and rotor flux estimator

has been designed using Extended Kalman Filter

(EKF) technique. With this choice, the sensor less

speed control scheme can achieve fast response as

good as that of drives with sensors, and at the same

time maintain a wide speed control range, with

kalman filter. The performance of the proposed

solution is simulated in Matlab environment.

KEYWORDS: Induction motor, Sensorless control,

Flux estimation, speed estimation, Kalman algorithm

1. INTRODUCTIONIn recent years, a large number of speed Sensorless

vector control systems for induction motor (IM) have

been proposed. Speed information is generallyprovided by a speed transducer on the motor shaft;

recently, low cost and high performance digital signal

processors (DSP) become available allowing obtaining

speed by means of digital estimators integrated with

motor control. This solution represents an advantage in

terms-of costs, simplicity and mechanical reliability of

the drive. Several schemes of speed estimators have

been proposed in the literature; among them, the

model reference adaptive system (MRAS) approach is

very attractive and gives good performance [1,2]. Theclassical MRAS method is based on the Adaptation of

the rotor flux [3, 4]; with this scheme, some

difficulties in terms of precise and robust speed

estimation arise, especially at low speed. The need of a

pure integration in the speed estimator represents a

drawback in the low speed region, due to drift and low

frequency disturbances; moreover, Parameter

sensitivity (in particular to stator resistance) representsa usual disadvantage for all model-based estimators

[5]. To overcome these problems, alternative MRAS

schemes based on back-EMF or reactive power [6]

have been presented, but it seems that they dont solve

troubles at low speed. The common approach to

increase dynamic performance and stability of speedSensorless field oriented control systems is the on-line

Parameter adaptation [7, 8, and 9].The main contribution of this paper is a novel

speed Sensorless vector control based on: a) a speed

and rotor resistance estimator, designed using EKF

technique, b) Indirect field oriented control (IFOC), c)

Suitable adjustments to improve robustness with

respect to parameter variations, measurement errors

and plant non-ideality. Rotor flux estimation andother compensations adopted allow enhanced

dynamic performance. Simulation results

illustrate the good performance of this solution,

also in the low speed region. Induction motors

are increasingly used in variable speed drive

applications with the development of vector

control technology [1, 2].There are two forms of

vector or field oriented control: directfieldorientation, which relies on direct measurement

or estimation of the rotor flux, and indirectfield

orientation, which utilizes an inherent slip

relation. Though indirect field orientation

essentially uses the command (reference) rotorflux, some recent works using the actual rotor

flux are reported to achieve perfect decoupling.

In many applications it is neither possiblenor desirable to install speed sensors from the

standpoints of cost, size, noise immunity and

reliability of the induction motor drive. So, the

Development of shaft sensor less adjustable

speed drive has become an important research

topic [9, 10]. There are two major concerns in the

sensorless speed control of induction motor

drive. One is the control scheme, and other one is

the estimation procedure. Both are highly

dependent on the motor parameters. Accurateestimation of flux and speed in the presence of

measurement and system noise, and parameter

variations is a challenging task. Kalman filter

named after Rudolph E. Kalman1 is one of the

most well known and often used tools for

stochastic estimation. An extensive literature on

Kalman filter and its applications is also

available [12]. The Kalman filter is essentially aset of mathematical equations that implement a

predictor-corrector type estimator that is optimal

in the sense that it minimizes the estimated error

covariance, when some presumed conditions are

met. For the flux and speed estimation problem

of induction motor, where parameter variationand measurement noise is present, Kalman filter

is the ideal one.In the present paper, inductionmotor model is reviewed in section 2. Input-

output linearization and decoupling scheme is

also discussed. In section 3, the Kalman filter for

flux and speed estimation is presented. Section 4

details the sensor less control scheme. Results

are discussed in section 5.

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2. INDUCTION MOTOR MODEL

From the voltage equations of the induction motor in

the arbitrary rotating d-q reference frame, the state

space model with stator current and rotor flux

components as state variables is8

11 12 1

021 22

A A Bi id s s

VSA Adt r r = +

Where

T

s ds qsi y i i = = ,T

r dr qr = T

s ds qsV V V =

11 1 ,eA a I J = 12 2 3 ,rA a I pa J =

52A a I=

1 0

0 1I

=

,

0 1

1 0J

=

(1)

( )2/ s rc Lr L L Lm= ,2 2

1 / ,s r ma cR cR L Lr = +2

2 / ,r ma cR L Lr = 3 4/ , / ,m r ra cL Lr a R L= =

5 / ,r m ra R L L=The torque developed by the motor is:

( ) ..........(2)T K i ie qs qr t dr ds = Where, torque constant, Kt=3PLm/2Lr, P-number of

pole pairs.

The speed dynamics of the motor is given as,

( )1 /r e rT T J = (3)Equations (1) and (3) describe the fifth order statemodel of the induction motor. In the motor model

described by eqns (1-3), nonlinearities and interactions

exist. The conditions required for decoupling control

of the motor are.

0, 0..........(4)qr qr = =

From (1), decoupling is obtained, when

. .............(5)qsr m

sl

r dr

iR L

L

=

The nonlinearity in the overall system are eliminated

by using input-output linear zing control

approach8.This approach consists of change of

coordinates and use of nonlinear inputs to linearize thesystem equations. Developed torque, Te is considered

as a state variable, replacing iqs to describe the motor

dynamics. Nonlinear control inputs U1 and U2 are

used to linearize8 the input voltages, vds, vqs to the

motor in terms of U1 and U2 are:

( )1 ................(6)1ds e qscV i u= +

.......(7)1 2

( )3u

V p i ar ds dr qs c Kt dr

= + +

The induction motor system with these new

inputs is decoupled into two linear subsystems:

electrical, and mechanical. The electrical

subsystem is described by eqns.

(8-9).

.....................(8)

.

1 2 1i a i a uds ds dr

= + +

( ).

4 4 .................(9)dr dr dsa a i = +

The mechanical subsystem is described by torque

and speed dynamic eqns. (10-11).

( ).

1 4 2 ..................(10)e r eT a a T u= + +

( )

.

/ ..................(11)r e l rT T J = The state space model of the electrical subsystem

is:

( ).

1 1 1 11 .................(12)x A x B u= +

1 1 1..................(13)y C x=Where X1= [ids dr]

T, y1-ids , B1= [1 0]

T , C1=[1

0]

The state model of the mechanical subsystem is:

( ).

2 2 2 2 2 2 .................(14)Lx A x B u D T = + +

2 2 2

..................(15)y C x=

Where X2= [Te r]T

, y2=Te , B2= [1 0]T , C2=[1

0]

D2=[0 -1/J]T

The rotor flux is estimated by applying The

Kalman Filter to discrete time form of eqns.

(12-13). The motor speed ris estimated by

applying the same algorithm to discrete timeform of eqns. (14-15). The Kalmans

algorithm for state estimation in linear systems

is explained in the next section.3. KALMAN FILTER FOR FLUX AND

SPEED ESTIMATION:

The discrete time model of both electrical

subsystem and mechanical subsystem is:

x(k+1)=F(k)x(k)+u(k). (16)y(k)=H(k)x(k)+w(k)(17)

Where, x(k) and y(k) are the state vector andoutput, respectively at the k-th sampling instant.

F(k) is the state transition matrix (22). is the

measurement matrix (12). is the random

disturbance input. It is the sum of physical input

and the system noise. w(k) is the measurement



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noise. Both u(k) and w(k) are assumed to be white

noise with zero mean.

Let, x^(k)=estimate of x(k) by Kamans algorithm

from the measurement of y(k)

x-(k)=extrapolated value of x(k) from the previousestimate, x^(k)

x^

(0)= priori estimate of x(k), or the initial guess ofx^(k)

P(0) = Error covariance matrix of initial guess x^(0)

The first step of Kalmans algorithm in estimating is to

determine the extrapolated value as follows:^

(1) (0) (0)x F x

=For a general notation at any sampling instant,

dropping the arguments:

..............(18)

^x F x

=Where, x^ is the previous estimate, and x-is the present

extrapolated value based on previous estimate.Theerror covariance matrix of the new x-is:

(1) (0) TP FP F Q

= +Again dropping arguments for a general notation,

..........(19)TP FPF Q

= +Dr. Kalman says the new optimal estimate is:

(^

( ..........(20)x x K y H x

= + Where, Kis the Kalman filter gainThe optimal gain of Kalman filter is given by12 :

( ) ..........(21)T T TK P H H P H R

= +

The new estimate x^has an error covariance matrix,which is given

( ) ( ) .........(22)T TP I KH P I KH KRK

= +The Kalman filter consists of repeated use of eqns .

(18-22) for each measurement.4. SENSORLESS CONTROL SCHEME

The block diagram of the sensorless speed control

scheme is shown in Fig. 1. This sensorless speed

control system consists of three major parts: P-I

controllers for speed and current, flux weakening

Controller, flux and speed estimator.

4.1 P-I Controllers for speed and current

One P-I controller is used for the flux, or flux

component of current as it is adequate for good

dynamic response. One P-I controller is used for the

speed control, and another for the torque, or torque

component of current. The reason for using two P-I

controllers (one for speed and the other for torque) in a

nested fashion is the significant difference in the time

constants of the speed and current, or theelectromagnetic torque. The design procedure for these

P-I controllers are detailed8. The gains are:

Kpd = 151.24, Kid = 43640, Kpw = 0.26, Kiw =

1.98, Kpq = 100, Kiq = 29877.

4.2 Flux weakening controller

The flux weakening controller is used to regulate

the magnitude of rotor flux linkage commandsuch that the motor will operate in constant

torque mode when motor speed is below base

speed and in constant power mode when motor

speed is above the base speed. The flux

weakening control algorithm is as follows.^

*^

^

...............(23)

rR b

dr brR b

r

if

if

=

where, r= rated rotor flux linkage in V s

b= base speed in rad/s,

r^

estimated rotor angular (mechanical) speedThe rotor flux command is then converted to an

equivalent field current command in the rotatingreference frame.

4.3 Flux and Speed Estimator

The flux and speed estimator using Kalman filter

is described in section 3. Only two voltage

sensors and two current sensors are used. Current

measurements are required for both estimation

and control purposes. But, voltage measurements

are taken only for control purpose. Measuredcurrents are transformed from 3-phase to rotating

d-q reference frame components, ids and iqs,

through the flux vector angle,e. Currentcomponent, ids is used to estimate the rotor flux

through eqns. (18-22). Then the estimated rotor

flux and the current component, iqs are used to

determine the developed torque, Te using eqns.

(2) and (4). The speed is estimated by Kalmanfilter eqns.(18-22) using this developed torque.

The estimated speed added with slip speed, givenby eqn.(5) is integrated to obtain the flux vector

angle,e Which is used in coordination



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transformation.

Fig 1: Block diagram of the sensorless speed control

scheme5.EXPECTED RESULTS AND DISCUSSIONS

The simulation study of the drive system has beencarried out with an induction motor whose rating and

parameters are given in Table 1.

Table 1 Rating and Parameters of the InductionMotor

Three phase, 50 Hz, 0.75 kW, 220V, 3A, 1440 rpm

Stator and rotor resistances: Rs = 6.37 ., Rr = 4.3

Stator and rotor self inductances: Ls = Lr = 0.26 H

Mutual inductance between stator and rotor: Lm=0.24 H

Moment of Inertia of motor and load: J = 0.0088 Kgm2

Viscous friction coefficient: = 0.003 N m s/rad

The rotor flux is estimated by Kamans algorithm.Using the estimated rotor flux speed is also estimated

by Kalman flter. Then the estimated rotor flux and the

estimated speed are used in the input-output

decoupling and linearizing control algorithm. The

simulation result is presented in Fig. 2, for flux and

speed estimation with a step decrease in speed

command from 1500 r/min to 1000 r/min. The

command flux linkage is 0.45 Vs. The estimatedspeed is similar to the actual speed response, except

the temporary deep of 27r/min. The actual rotor flux,

estimated rotor flux and error in estimation of flux and

speed are also shown. For a step increase in speed

command from 1500 r/min to 1800 r/min withweakening of command flux linkage from 0.45

Vs to 0.375 Vs, the simulation result is presented in

Fig. 3. The Estimated speed is similar to the actualspeed response, except the temporary spike of 18

r/min.

Fig 2.Simmulation response for speed and flux

estimation with step change in speed: (a)Actual

speed,(b)Actual Rotor flux linkages,(c)Estimated

speed,(d)Estimated Rotor Flux Linkages, (e)

Error in estimated speed, (f) Error in EstimatedRotor Flux Linkages

FIG 3. Simulation response for speed and flux

estimating with step increase in speed and flux

weakening (a) Actual Speed,(b) Actual Rotor

Flux Linkages,(c) Estimated Speed, (d)Estimated

Rotor Flux Linkages,(e) Error in estimatedSpeed,(f)Error in Estimated Rotor Flux Linkages.



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6. CONCLUSIONS

The estimation of rotor flux and speed of induction

motor, using Kalman filter is presented. Torque and

rotor flux are decoupled and the induction motor

model is linearize using input output linearizationapproach. Rotor flux and speed are estimated by

Kalman filter. Sensorless control of the linearize anddecoupled drive using estimated flux and speed, is

simulated and results presented. Kalman filter is found

to be very good and fast for flux and speed estimation

in the presence of system and measurement noise. The

dynamic response of the sensorless drive is as fast as

that of drives with physical sensors. Sensorless speedcontrol scheme works for a wide speed control range.

7.REFERENCES

[1] K. S. Narendra and A. M. Annaswamy. StableadaptiveSystems. Englewood Cliffs, NJ: Prentice-Hall,

1989.

[2] Y. D. Landau. Adaptive control - The model

referenceapproach. Marcel Dekker Inc., 1979.[3]Colin Schauder. Adaptive speed identification for

vectorcontrol of induction motors without rotationaltransducers.IEEE Trans. Indust. Appl., 28(5):1054

1061, Set1992.

[4] H. Tajima and Y. Hori. Speed sensorless field-

orientation control of the induction machine. IEEE

Trans. Indust.Appl., 29(1):175180, Jan/Feb 1993.

[5]R. Blasco-Gimenez, G. M. Asher, M. Sumner, and

K.J.Bradley. Dynamic performance limitations for

MRASbased sensorless induction motor drives. Part 1:Stability analysis for the closed loop drive. IEEE Proc.

Electr.

Power Appl., 143(2):113122, Mar 1996.[6] Fang-Zheng Peng and Tadashi Fukao. Robust

speed identification for speed-sensorless vector control

of induction motors. IEEE Trans. Indust. Appl.,

30(5):12341240, Sep/Oct 1994.

[7] W. Leonhard, Control of Electrical Drives,

Springer-Verlag, Berlin, 1990.

[8] D. W. Novotny,and R. D. Lorenz (eds.),

Introduction to Field Orientation and High

Performance AC Drives, IAS Annual Meetings:Tutorial book, IEEE, 1986.

[9]H. Kubota, and K. Matsuse, Flux observer of

induction motor with parameter adaption for widespeed range motor drives, Proc. IPEC, pp. 1213-

1218, Tokyo, 1990[10] Y. Hori,V. Cotter,and Y. Kaya, A novel

induction machine flux observer and its application to

a high performance ac drive system, Procc. of 10th

IFAC World Congress, IFAC, Munich, July

1987.

[11]G.C.Verghese,and S. R. Sanders, Observers

for flux estimation in induction machines, IEEE

Trans. on Indust. Elec, vol. 35, no. 1, pp. 85-94,1988.

[12] P. L. Jansen, and R. D. Lorenz, Aphysically insightful approach to the design and

accuracy assessment of flux observers for field

oriented induction machine drives, IEEE Trans.

on Ind. Appl., vol. IA-30, no.1, pp. 101-110,

1994.

[12]. Y. Hori, and T. Umeno, Flux observerbased field orientation (FOFO) controller for

high performance torque control, Proc. IPEC,

pp. 1219-1226, Tokyo, 1990.

[13] K. B. Mohanty, Study of DifferentControllers and Implementation for an Inverter

Fed Induction Motor Drive, Ph. D. Thesis, IIT

Kharagpur, May 2001.

[14] K. Ohnishi, N. Matsui, and Y. Hori,Estimation, identification and sensorless control

in motion control system, Proc. of IEEE, vol.82, no. 8, pp. 1253-1265, Aug. 1994.

8. BIOGRAPHIES

K.Bhaskar, He received B.Tech. in Electrical and

Electronics Engineering from N.I.T

WARANGAL in 2006 and perusing M.Tech

(2006-2008)in Electrical Engineering from

Chaitanya Bharathi Institute ofTechnology(PS&PE) (C.B.I.T).

K.Krishnaveni, she is working as ASSOCIATEPROPESSOR in Chitanya Bharathi Institute of

technology, gandipeta (Hyderabad) she has

presented a thesis On FLEXIBLE A.C.

TRANSMISSION SYSTEMS in J.N.T.U

HYDERABAD



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2. Modelling and Simulation of Interline Power Flow

ControllerD. Ravishankar, Dr. K.Udayakumar, professor

AbstractAn Interline power flow controller is VSC

based FACTS controller for series compensation with

unique capability of power flow management

among multi lines with

in same corridor of a transmission line. FACTS

controllers can control series impedance, shunt

impedance, current, voltage and phase angle. Real power

can be transferred via common dc-link between the

VSCS and each VSC is capable of exchanging reactive

power with its own transmission system .In this paper,

the different controller circuit models of IPFC is modeled

and simulated in PSPICE software package and the

power balance between two transmission lines is clearly

analyzed.

Index Termsflexible ac transmission, static

synchronous series compensator ,interline power flow

controller

1. INTRODUCTION

HE ac transmissible power can be approximated

as P=(Vs*Vr*sin )/X .Suitable adjustments of any

of these parameters can achieve power flow control.

Mechanical switches based traditional approaches

cannot realize full utilization of transmission system

due to large stability margin. FACTS controllers can

be grouped into two typesThyristor controlled

FACTS controllers and VSC based FACTS controllers

.Power electronic based FACTS controllers can

internally generate both real power and reactive power

without the use of ac capacitors or reactors andfacilitate both real power and reactive power flow.

[1,2]VSC based FACTS controllers include static

synchronous(

T

compensator(STATCOM),for shunt reactive power

compensation static synchronous series compensator

(SSSC)for series reactive power compensation, unified

power flow controller (UPFC) with unique capability

of independently both the active and reactive power

flow in the line and interline power flow controller.

[2,3,4]

The interline power flow controller(IPFC) Concept

compensates the problem of compensating a number

of transmission lines at sub station .the IPFC consistsof two or more SSSC with a common dc link ,so,each

SSSC contains a VSC that is in series with the

transmission line through a coupling transformer and

injects a voltage with controllable magnitude and

phase angle. IPFC provide independent control of

reactive power of each individual line , while active

power could be transferred via dc link between

compensated lines. An IPFC used to equalize

active/reactive power between transmission lines

and transfer power from overloaded lines to

under loaded lines.[10]

2. BASIC CHARACTERISTICS OF IPFC

The interline power flow controller employs a

number of dc to ac inverters each providing series

compensation for a different line. and the

compensating inverters is shown in fig 1.

Fig1.interline power flow controller (ipfc)

comprising n converters

Fig.2.Schematic diagram of two-converter IPFC.

Consider an IPFC scheme consisting of two

back to back dc to ac inverters, each



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compensating a transmission line transmission systems

employ self commutated inverters as synchronous

voltage sources .the power electronic based voltage

sources can internally generate and absorb reactive

power without the use of capacitors and inductors

.they can facilitate both real and reactive power

compensation and can independently control real andreactive power flow.

Fig.3.

basic two inverter interline power flow controller

Consider an IPFC scheme consisting of two back toback inverters each compensating a transmission line

by series voltage injection. the arrangement is shown

in FIG.3where two synchronous voltage sources V1pq

&V2pq,in series with transmission lines 1 and

2represent to back to back inverters .the common dc

link is represented by directional link for real power

exchange between voltage sources. the sending and

receiving voltages are assumed to be

equal.V1s=V2s=V1r=V2r=1.0p.u. with fixed angles

resulting in identical transmission lines with fixed

angles 1= 2=30.for two systems.[2]

The System 1is selected to be prime system for which

controllability is real power and reactive power is

stipulated. the reason for stipulation is free

controllability of system 1imposes on power control of

system 2.[2]

.fig 4 phasor diagram ofsystem1

. fig4 is phasor diagram defining relationship

between V1s,Vx1and inserted phasor V1pq.the

inserted voltage is added to fixed end voltage phasor

v1s to produce the effective sending end

voltage .as r1 is varied over 360 range the locus

moves along a circle with its centre at end of v1s.

3. MODELLING OF IPFCA SSSC is VSC based FACTS controller for

series power injection and IPFC is a combination

of two SSSCs. Coupled with common DC linkfor two identical transmission lines. So here a

VSC based FACTS controller SSSC which is

apart of IPFC with a transmission line is

modeled. The power control and Receiving end

voltage varies with the variation of firing angle is

analyzed. A transmission line is modeled as

series R,L and it is terminated with a load .the

VSC based FACTS controller is modeled and

connected to transmission line. the voltage

variations are clearly analyzed.

0

D 7

L 2

3 0 m H

1 2

V 5

L 3

1 0 0 m H

1

2

L 4

3 0 m H

1 2

0

D 8

V 3

+

-

+

-

S 1

S

0

R 2

. 0 0 1

21

+

-

+

-

S 2

S

0

+

-

+

-

S 4

S

0

V 4

-+

+-

E 1

E

V 2

V 6

F R E Q = 5 0

V A M P L = 1 1 0 0 0

D 5

R 5

4 2

2

1

V 71 0 0 0 V d c

0

D 6

+

-

+

-

S 3

fig5. a transmission line model with SSSC(a part

of IPFC)A transmission line shows improved

receiving end voltage and power handlingcapability is increased.

4..SIMULATION RESULTS

The interline power flow controller two

identical transmission lines(impedance, torque

angle, voltage).upper line operating at

11Kv(overloaded) and lower line under loaded

10kv.when it is uncompensated IPFC is disabled

and it is enabled when two transmission lines are

connected diode bridge and VSC based converter

.coupled with DC link and connected with

current controllers and voltage controllers.



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V 5

V 4

0

V 2

0

0

+

-

+

-

S 2

S

C 1

5 0 m

1

2

D 3

0

R 2

. 0 0 1

21

L 1

3 0 m H

1 2

D 1

+

-

H 1

H

D 4

0

V 3

L 5

3 0 m H

1 2

V 6

F R E Q = 5 0

V A M P L = 1 0 0 0 0

V O F F = 0

R 1

1 0

2

1

L 6

1 0 0 m H

1

2

R 5

1 0

2

1

L 3

1 0 0 m H

1

2

D 2+

-

+

-

S 3

0

L 4

3 0 m H

1 2

0

L 2

3 0 m H

1 2

R 3

. 0 0 1

21

+

-

+

-

S 4

S

+

-

+

-

S 1

S

V 1

F R E Q = 5 0

V A M P L = 1 1 0 0 0

V O F F = 0

-+

+-

E 1

E

Fig

.6.two compensated lines i.e. with IPFC enabled

T i m e

2 . 9 0 s2 . 9 1 s2 . 9 2 s2 . 9 3 s2 . 9 4 s2 . 9 5 s2 . 9 6 s2 . 9 7 s2 . 9 8 s2 . 9 9 s3 . 0

V ( V 1 : + , 0 )V ( L 5 : 2 , 0 )

- 2 0 K V

0 V

2 0 K V

Fig.6.receiving end voltages with IPFC disabled

Under uncompensated IPFC disabled condition

for the two lines upper and lower sending end

voltage, receiving end voltage, load power

across resistor and inductor recorded. It is

observed that the lower line delivers lower

power to the load. To correct the under loaded

condition power is tapped from the upper line

to enable lower line to deliver normal powerto load

T i m e

2 . 9 0 s2 . 9 1 s2 . 9 2 s2 . 9 3 s2 . 9 4 s2 . 9 5 s2 . 9 6 s2 . 9 7 s2 . 9 8 s2 . 9 9 s3 . 0

V ( V 6 : + , 0 )V ( L 4 : 2 , 0 )

- 1 0 K V

0 V

1 0 K V

fig6b.receiving end voltages withIPFCenabled delayed by 90 degrees

Influence of the Compensation voltage

depends on two factors (i) Magnitude of DC

link voltage, (ii) Vector position of thecompensation voltage with respect to the line

current.

T i m e

2 . 9 0 s2 . 9 1 s2 . 9 2 s2 . 9 3 s2 . 9 4 s2 . 9 5 s2 . 9 6 s2 . 9 7 s2 . 9 8 s2 . 9 9 s3 . 0

V ( R 2 : 2 , 0 )V ( L 2 : 1 , E 1 : 4 )V ( L 2 : 1 , 0 )

- 2 0 K V

0 V

2 0 K V

Fig6c.lower end sending end voltage

compensation voltage and resultant voltage

For easy simulation vector position of injected

compensation voltage is referred with respect to

the sending end voltage. Four cas

considered. (i) -90 (ii) -180 (iii) -270 (iv)0Cases ..so, in this paper the firing angles arevaried from 0 to 360 and it was observed thatvariation of firing angles from 0 to -180 online-2 (under loaded)P2 2(under loaded)P2 and

Q2 increases. Attains a maximum value between

-270 and 0line -2 power transfer capabilityincreases due to IPFC dc link. both real and

reactive power increases and voltage levels of

line-2 increases.



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TABLE.1. results for various firing angles.

comp V1s V2s V1r V2r P1 P2

-90 11 10 8.5 8.5 1.1 0.9-180 11 10 8.5 6.5 1.1 0.6-270 11 10 8.5 9 1.1 0.9

0 11 10 8.5 9 1.0 1.2

5. SIMULATION OF CLOSED LOOP IPFC

SYSTEM

In the control circuit the ac voltages are rectified using

diode bridge rectifiers. The outputs of rectifiers are

attenuated using potential dividers .The outputs of

lines 1&2 are applied to the

D 1 9

M U R 1 5 0

D 2 0

M U R 1 5 0

R 1 7

2 . 5

C 2

4 0 0 0 u

-

++

-

E 6

E

D 1 4

M U R 1 5 0

L 7

1 1 . 5 m

1 2

R 1 6

2 . 5

V 3

F R E Q = 5 0

V A M P L = 1 0 0 0 0

V O F F = 0

R 1 4

1 0

V 1

F R E Q = 5 0

V A M P L = 2 0 0 0

V O F F = 0

T D = 1

R 2 0

0 . 1 k

R 2 1

9 9 . 9 k

F 2

F

0 . 0 9 k

0

R 1

1 0 0 0 k

L 6

1 1 . 5 m

1 2

0

0

0

R 2 6

1 k

L 9

1 5 m

1

2

D 1 3

M U R 1 5 0

D 1 8

M U R 1 5 0

R 1 9

9 9 . 1 k

R 1 2

2 . 5

+-

H 6

H

R 2 5

3 0 0 0 0

R 1 5

1 0

+

-

+

-

S 6

S

V O N = 2

V O F F = 0 . 0 V

D 1 6

M U R 1 5 0

R 2 4

3 0 k

L 5

1 1 . 5 m

1 2

0

0

D 1 7

M U R 1 5 0

U 2

O P A M P

+

-

O U T

L 8

1 5 m

1

2

D 1 5

M U R 1 5 0

R 2 21 k

0

L 4

1 1 . 5 m

1 2

C 3

4 0 0 0 u

0

V 4

F R E Q = 5 0

V A M P L = 1 0 0 0 0

V O F F = 0

R 2 3

1 k

R 1 3

2 . 5

.Fig7a.closed loop IPFC system.

differential amplifier. IPFC is enabled when the voltages

are different .The circuit model of closed loop system is

shown in fig 7a .The voltage across the switch S is shownin fig 7b.

Time

0s 0.5s 1.0s 1.5s 2.0s

W(L8)

-40MW

-20MW

0W

20MW

40MW

Fig7b.voltage across switch

Real powers in lines 1&2 are shown in

Figures7c&7d.The reactive power through lines

1&2 are shown inFigures 7e & 7f respectively.

From the above Figures, Itcan be observed that the

real power increases when theIPFC is enabled

Time

0. 85 0s 0.9 00 s 0. 95 0s 1.000 s 1. 050s 1.1 00s 1. 15 0s0.814s 1.191s

W(R14)

0W

1.0MW

2.0MW

3.0MW

4.0MW

Fig7c.real power of the 1st line

T im e

0 . 8 8 0 0 s 0 . 9 2 0 0 s 0 . 9 6 0 0 s 1 . 0 0 0 0 s 1 . 0 4 0 0 s 1 . 0 8 0 0 s 1 . 1 2 0 0 s0 . 8 49 6 s

W( R 1 5 )

0 W

5 0 . 0M W

1 0 0 . 0 M W

1 4 9 . 7 M W

--

fig7d.real power of the 2nd line



11/58

T i m e

0 . 9 0 0 s 0 . 9 5 0 s 1 . 0 0 0 s 1 . 0 5 0 s 1 . 1 0 0 s 1 . 1 5 0 s 1 . 2 0 0 s0 . 8 6 1 s

W ( L 9 )

- 1 . 0 M W

- 0 . 5 M W

0 W

0 . 5 M W

1 . 0 M W

Fig7e.reactive power of line1

Ti m e

0 .9 0s 0. 9 5s 1. 00 s 1 .0 5s 1.1 0s 1. 15s 1 .2 0 s

W (L 8 )

-4 0.0M W

-2 0.0M W

0 W

20. 0M W

39. 7M W

fig7e.reactive power of line 2

VI.CONCLUSION

The FACTS controller IPFC to be located at the

sub-station for a transmission system with more than

one line can corrects the imbalance on account of line

over-loading and under-loading to enable transmission

lines to be operated up to its thermal limits without

compromising the stability Circuit model with variousfiring angles and various voltages were simulated to

study the real and reactive power flows. The circuit

model for open loop and closed loop systems are

presented..It is observed that the real and reactive

powers are increased by the presence of IPFC.

References

[1].L.Gyugyi, Application Characteristics ofConverter-Based FACTS Controllers, International

Conference on PowerCon 2000, Vol.1, pp.391~396

[2] L.Gyugyi, K.K.Sen, C.D.Schauder, The InterlinePower Flow Controller Concept: A New Approach toPower Flow Management in Transmission Systems,IEEE/PES Summer Meeting, Paper No. PE-316-

PWRD-0-07-1998, San Diego, July 1998

[3] L.Gyugyi, K.K.Sen, C.D.Schauder, The InterlinePower Flow Controller Concept: A New Approach to

Power Flow Management in Transmission Systems,IEEE Transactions on Power Delivery, Vol. 14, No. 3,pp.1115~1123, July 1999.

[4] I.Papic, P.Zunko, D.Povh, M.Weinhold, BasicControl of Unified Power Flow Controller, IEEETransactions on Power Systems, Vol. 12, No. 4,pp.1734~1739, Nove

[5]Jianhong Chen, Tjing T.Lie.D.M.Vilathgamua.Basic Control Interline Power Flow Controller:, IEEE

Trans, 2002.

[6] I.Papic, P.Zunko, D.Povh, M.Weinhold, BasicControl of Unified Power Flow Controller, IEEE

Transactions on ower Systems, Vol. 12, No. 4,pp.1734~1739, November 1997.

[7] I.J.Nagrath and D.P.Kothari, Modern Power

System Analysis, Second Edition, Tata McGraw-Hill

Publishing Company Limited, NewDelhi.

[8] G.K.Dubey, S.R.Doradla, A.Joshi and

R.M.K.Sinha, Thyristor Power Controllers, NewAge International(P) Limited, Publishers, New Delhi-110002.

[9] Jianhong Chen, Tjing T.Lie.D.M.Vilathgamua.Basic Control Interline Power Flow Controller:, IEEETrans, 2002.



12/58

3. ANALYSIS OF CHOPPER FED D.C. DRIVE WITH PWM &

HYSTERESIS CURRENT CONTROL SCHEME* MAULIK. R. DHANDHARA ** SABHA RAJ ARYA

ABSTRACT- The work presented in thispaper deals with the analysis of choppercontrolled DC drive. Performance of DCdrive with open loop (conventional andPWM) and closed loop has been done. Afteranalysis, it is found that using choppercircuit in open loop does not give accurateresult as compared to theoretical value aswell as in terms of quality. To avoid thisdraw-back, closed loop control system istaken for drive control. Using Hysteresiscurrent control, it is observed that

performance has been improved andoutput characteristics are satisfactory.Key word: chopper, PWM, Hysteresis current

control

INTRODUCTION In DC shunt motor the speed isapproximately a constant speed. The speed dropfrom no load to full load is generally less than 5 to6%. called as constant speed motor. In aseparately excited dc motor the field winding isseparately connected to an external source. Thismotor are almost exclusively used for variablespeed drive as it can be easily adopted to theload requirement. Different type of control forspeed are used i.e. field control armature voltagecontrol etc. But armature voltage control methodare generally used. The speed regulationdepends on the armature circuit resistance whichis practically very less. The speed torquecharacteristics of this motor is a straight line i.e.the speed decreases with increasing in load. Thistype of motor are used where good speedregulation and adjustable speed is required. Ithas wide range of speed control.-----------------------------------------------------------*MAULIK.R.DHANDHARA (M.Tech.student),**SABHARAJ ARYA (Lecturer),

*** Mrs. V.A. SHAH(Asst. Professor) SVNIT SURAT-395001

Elementary Chopper circuit

Fig 1( a & b)-chopper circuit & output parameter

chopped load voltage as shown in figure(1) is obtained froma constant D.C supply of magnitude VS. During the periodTon, the chopper is on and Vo= VS . During the interval Toff,chopper is off, load current flows through the free wheelingdiode and Vo is zero, a chopped d.c voltage is produce at

the load terminal in continuous. sVToffTon

TonV .0

+=

sV.= , sVTonfV ..0 =

where is called duty cycle, f= chopping

frequency.

CONTROL STRATEGIES

Output voltage Vo can be controlled through by openingand closing the semiconductor switch periodically.



13/58

(a) Const frequency System :Ton is variedbut chopping frequency f is kept constant.adjustment of Pulse width as such thisscheme is also called Pulse width modulation scheme or time ratio control(TRC) scheme,.

(b) Variable frequency Scheme The

chopping frequency f is varied and eitherTon of Toffis kept Const. this method ofcontrolling is also called frequencymodulation Scheme High efficiency of 70%to 95% are typically obtained usingswitched-mode, or chopper, circuits. Pulse-width modulation (PWM) allows control andregulation of the total output voltage. Abasic dc-dc converter circuit known as thebuck converter is illustrated in Fig.1. AnSPDT switch is connected to the dc input

voltage gVas shown. The switch network

changes the dc component of the voltage.Since 0 D 1, the dc component of sV is

less than or equal to gV . In addition to dc

voltage component sV, )(tVs contains

undesired harmonics of the switchingfrequency. A low-pass filter is employed for thispurpose converter of Fig. contains a single-section L-C low-pass filter. The filter has corner

frequencyLC

f2

10= .

the conversion ratio M(D) is defined as the

ratio of the dc output voltage V to the dc input

voltage gV under stead-state condition:

gV

VDM =)( For the buck converter, M(D) is

given by M(D) = D

When (t) is high (for 0< t < DTs), thenMOSFET Q1 conducts with negligible drain-to-source voltage. Hence, Vs(t) is approximatelyequal to Vg , and the diode is reverse-biased. The

positive inductor current i1(t) flows through theMSOFET.control system: control system can be constructed.that varies the duty cycle to cause the output voltage to

follow a given reference rV Figure(2) shown below

illustrates the block diagram of a simple converterfeedback system

.

Fig(2) PWM CONTROLLING SCHEME

The output voltage is sensed and is compared with a refere

voltage rV . The resulting error signal is compensated to de

analog voltage )(tVc . The pulse-width modulator produce

switched voltage waveform that controls the gate of the poswitch Q1. If this control system is designed such that duty cy

automatically adjusted and v follows the reference voltage

independent of variations in gV or load current.

CHOPPER CONTROL DC DRIVE

the constant-voltage d.c supply input allows impropower factor and wave form of A.C side. Also the relatively chopping frequency employed permits reduced ripple curwhich ensures better motor performance as well as reduced lay in the system response due to the lower value of inductance required. However energy is lost at each commutaand the efficiency of the chopper decreases as the chop

frequency is increased.

In CLC , is varied in directly by controlling the mcurrent between certain specified maximum and minimum valIn effect, this type of control is a variable frequency convariable on-time and off-time. The diagram of a chopper fed motor load is shown in below.

Chopper control of separately excited dc moto:

A chopper controlled separately excited dc motor drivshown in Fig.(3)

Raia + La dia/dt+ E=V, 0 t ton

In this interval, armature current increases from ia1to ia2.Since motor is connected to the source during this interval.Which is called duty interval.



14/58

Figure(3): - Chopper Control of Separately

Excited DC Motor

Raia + La dia/dt+ E=0, ton t T

Motor current decreases from ia2 to ia1 during thisinterval.

From Fig. (3) ==ont

a VdtT

V0

1V

Now we have

Ia = ( V- E) / Ra , m = V/ K RaT/K2

Banking Va

Motoring

Regenerative

increasing

fig(4)The nature of speed torque characteristics

CONTROL SCHEME AND COMPONENTS

Principle of the PWM DC motor drive

The permanent magnet DC motor may be represented by s

L/R ratio.

Average motor current is a function of the electrical time cons

of the motor, a, where. a = L/R For a PWM waveform

period T the ratio of pulse width to switching period is denote . The average pulse current will depend upon the ratio of

current pulse width, T, to the motor electrical time constant,

Fig(5) instantaneous motor current waveforms

Figure5 (a) High inductance motor & Figure 5(b) Low induc

motor .

Motor which has high armature inductance will require a lo

PWM drive frequency in order to establish the required c

levels, and hence develop the necessary torque. A low inducta

motor allows the use of a high switching drive frequency

resulting in an overall faster system response, the printed ci

motor is one of the lowest inductance DC motors availa

electrical time constants in the order of 100 us, allow these mo

to be used with switching rates as high as 100kHz, with typ

drive circuits being operated at 10kHz.Motor current control,

hence torque control, is achieved by varying the width of

applied pulsed waveforms. This is done in open look as well a

closed loop situation. . Open loop situations are situations in w

duty ration is fixed but closed loop situations are those in which

duty ratio not necessarily is fixed but may depend on the stat

converter. For the close loop case amounts to computat


Va

b) Va

Vdc

Vdc

ia

ia

TdT


15/58

are numerically far less involved than the computations

in averaging. The computations can easily be perform

also including higher harmonics.

PWM Motor control: The current in the motor

winding rises exponentially at a rate governed

mainly by average supply voltage and motor

inductance. If the pulse width is close to the time

constant of the motor then the current at the end

of the first pulse will reach nearly 60% of its

maximum value, lmax = Vdc/Ra . This is Sown as l1 in

fig.4. For the remainder of the PWM cycle switch

S1 is off and motor current decays through the

diode at a rate dependant upon the external

circuit constants and internal motor leakagecurrents, according to the equation:

att

a eIi /)(

1

=

The motor current at the end of the period, T,

remains at a level l2, which is then the starting current

for the next cycle, as shown in Fig.(6)

va

tIa

t

Fig. (6) Motor current waveforms at start-up

As the switching sequence repeats, sufficient current

begins to flow to give an accelerating torque and thus

cause armature rotation. As soon as rotation begins,back emf is generated which subtracts from the supply

voltage.

The motor equation then becomes:

La. di a / dt + Ra. ia = V - Ea

The current drawn from the supply will consequently be less

that drawn at start-up due to the effect of the motor back emf t

Ea. For a given PWM duty cycle ratio, , the motor reach

quiescent speed governed by the load torque and damping fric

Maximum motor torque is required at start-up in order to accelethe motor and load inertias to the desired speed. The cur

required at start-up is therefore also a maximum. At the end of

starting ramp the controller duty cycle is reduced because

current is then needed to maintain the motor speed at its ste

state value.

Fig (7) MOTOR CURRENT WAVEFORM, Ta


16/58

straight slopes, and by the infinite power supply

rejection ratio PSRR, if the supply variation can be

considered by very slow compare by the switching

frequency. Power supply variation at higher frequencies

are not suppressed totally, and will result in sum and

difference products of the reference signal and the

power supply variation, but these steel meets high

suppression for use in audio amplifier applications the

hysteresis controller is very desirable due to the high

linearity and simple design. However hysteresis

controller suffers from a switching frequency dependent

on the modulation index, M, of the amplifier. All other

types of self oscillating modulator suffers this

phenomena too.The basic operation of the current mode hysteresis

operation is : The out put inductor integrates the

differential voltage between the out put voltage of the

power stage and the out put voltage of the amplifier. If

the out put voltage of the amplifier can be considered

constant within one switching period the integration

results in a saw-tooth shaped inductor current, which is

subtracted from the reference current programming

voltage, and fed into a hysteresis window to control theswitching frequency by controlling the time delay

through the controller loop. In hysteresis control, the

power converter O/P is monitored an active switch

operates as the O/P crosses the threshold. The

simplest technique is to compare the O/P to a reference

wave form, Switching on when the O/P is too low and

when it is too high.

The current is controlled with in a narrows band

of excursion from its desired value in the hysteresis

controller. The hysteresis window determines the

allowable or present deviation of current

Commanded current and actual current are shown in

the fig. with the hysteresis windows. The voltage

applied to the load is determined by the following logic.

ia ia - i , Set Va =Vs

ia ia+ I , Reset Va = o

Fig(8): HYSTERESIS CONTROLLER OPERATION

The disadvantages of this controller is higher Switching loss du

the high switching frequency. Hysteresis control is inher

Robust, Since the Switchs Operate to enforce a desired

irrespective of time scale or line or load values. There are

fundamental limitations but (a low voltage i/p bus can force on

limited current slew rate on inductor for instance), but hyster

can help keep a converter near any feasible operating condi

The loop gain function is

)(*

)(

sia

sia= K

)1(*)1)(1(

)1(

21 STrKHSTST

ST

C

M

++++

+

Where K=Kc*Kr*Ki ,TM= mechanical time const

,Tr=converter time delay

Speed feed back filter is used in the control system. The

parameter of filter which are in the MATLAB simulation

programme are the combination parameter of

generater & filter. The transfer function of speed feed back

filter is G(s)=H / (1+ST) =0.065/(1+0.01s)

RESULTS:



17/58

SIMULATION OF CHOPPER FED DC DRIVE WITH

PWM CONTROL

The simulation results such that the out put of the DC

drive with PWM control (Armature speed, Armature

Current & Out put electro magnetic torque ) are shown

in figure. Both steady state and ripple present in the

speed current and torque at no load condition also

shown in the result figure(9).

(a)Speed variation of PWM control dc motor started

with no load

(b)Current variation of PWM control dc motor started

with no load

(c) Speed variation when full load (4.54 Nm) is

applied suddenly

(d) Current variation when full load (4.54 Nm) is appli

suddenly

Fig(9) Drive behavior in PWM control under

application.

SIMULATION FOR CHOPPER FED DC DRIV

HYSTERESIS CURRENT CONTROL

A simple chopper dc drive with hysteresis control is designe

and simulated in MATLAB . result are shown in fig (1

different load

(a) Speed variation of dc motor started with no load

(b) Speed variation when full load (4.54 Nm) is applied

suddenly

(c) Current variation when full load (4.54 Nm) is applied

suddenly

Fig.. (10) Drive behavior in Hysteresis current control under

sudden load application.



18/58

The simulation results such that the out put of

the DC drive with Hysteresis control (Armature speed,

Armature Current & Out put electro magnetic torque )

are shown in figure. Both steady state and ripple

present in the speed current and torque at no load

condition also shown in the result fig.(10).

Comparison: the comparison table between theoretical

value are shown in table (1)

Speed &

current

No load Half load Full load

Theoretical

value

175.4

rad/sec

- 166 rad/sec

0.69 amp. - 5.1 amp.PWM

control

175.20

rad/sec

167.16

rad/sec

161.235

rad/sec0.68 amp. 2.6 amp. 5.1 amp.

Hysteresis

current

control

174

rad/sec

174.95

rad/sec

174.93

rad/sec

0.61 amp. 2.45 amp. 5.1 amp.

Table (1) : CONCLUSION AND SCOPE FOR

FUTURE WORK:

The simulation work of gate pulse, PWM and hysteresis

current control of chopper fed separately excited d.c

motor drive, demonstrates that the hysteresis control is

more accurate control among the three scheme and is

able to over come the disadvantages of gate pulse and

PWM control of d.c motor drive. This improve

performance is possible due to the current control in the

hysteresis band i.e. the out put of motor compares with

a reference waveform and the chopper switch is on

when the output is low or off when the output is high.

The deviation in speed incase of hysteresis currentcontrol as compare to the ideal case is very less. In

hysteresis current control output characteristics is

uniformed but in case of pulse , it is non uniform and in

PWM it is intermediate. This hysteresis control is

possible only in buck converter.

In this work separately excited d.c motor drive with

control strategies are simulated using SIMULINK tool bo

MATLAB Software Package. This control can also be applied

real drive by using Hardware.

REFERENCES:

1 . B.H. KHAN, G.K.DUBEY & SESHAGINI R. DORADLA, ANECONO

FOUR-QUADRANT GTO CONVERTERANDITSAPPLICATIONTO DC DRIVE, I

TRAN. ON POWERELECTRONICS, VOL. 8, NO. 1 JAN 1993.

2. JOACHIM HOLTZ & BERND BEYER, FAST CURRENT TRAJECTORY TRAC

CONTROL BASEDON SYNCHRONOUS OPTIMAL PULSE-WIDTH MODULAT

IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING, DENVER, 1994

3. AKIRA NABAE, SATOSHI OGASAWARA & HIROFURNI AKAGI, A NOVEL

CONTROL SCHEMEFOR CURRENT CONTROLLER PWM INVERTER,IEEE TRAN. ON INDUSTRY APPLICATIONS VOL. IA-22, NO. 4

JULY/AUGUST 1986.

4. LUIGI MALESANI, PAOLO MATTAVELLIAND PAOLO TOMASIN, IMPROVED

CONSTANT

FREQUENCY HYSTERESIS CURRENT CONTROLOF VSI INVERTERSWITH.

SIMPLE FEEDJRWARD

BANWIDTH PREDICTION, IEEE TRAN. ON INDUSTRY APPLICATIONS,

VOL. 33, NO. 5,

SEP/OCT 1997.5. PROF. STVAN NAGY & ZOLTAN SUTO, NON-LINEAR PHENOMENONIN

CURRENT CONTROL ()FIFLDUCTIOFL MOTOR, IEEE PRESS, PP 328-

33 1.

6. JOCOVE W. VANDER WOUDE, WILLEM L. DE KONING & YUSUFFUAD,

THE PERIODIC BEHAVIOROFPWM DC- DC CONVERTERS, IEEE TRAN

POWER ELECTRONICS, VOL. 17, NO. 4, JULY 2002.

7. SOREN POULSENAND MICHAEL A. E. ANDERSEN, HYSTERESIS CONTRO

WITH CONSTANT SWITCHING FREQUENCY.

8. ROBERT W. ERICKSONDRAGAN MAKSIMOVIC, FUNDAMENTALSOFP

ELECTRONIC 2NDEDITION 2001, PAGE 657-659.

9. N. MOHAN, T. UNDELAND, W. ROBBINS, POWERELECTRONICS. CONVER

APPLICATIONS, DESIGN, 3 EDITION, NEW YORK: JOHN WILEY & SONS 2003

10 . R. KRISHNAN ELECTRICMOTOR DRIVES MODELING ANALYSISANDCON

1 STEDITION



19/58

2003.

11. PROF DR. M. MARARI, DR. F.J. KRAUS, CONTROIOF

SEPARATELYEXCITED D.C. MOTOR,AUTOMATIONCONTROL

LABORATORY, SUMMERTERM 2005.

12. VEDARN SUBRAHMANYAM , ELECTRICDRIVE , CONCEPT &

APPLICATION , TATA MCGRAW- HILLPUBLISHINGCOMPANYLTD. 9T1

EDITION 2002



20/58

APPENDIX

Data considered for simulation(PWM)

For 1 H.P. DC motor (From the machine

calculation)

Armature resistance = Ra=3

Armature inductance = La=56mH

Field resistance= Rf= 570

Field inductance = Lf=13.5H

Mutual inductance = 2.75 H

Moment of inertia J= 0.1kg-m2

Frictional constant = Bt = 0.03 N.m / (rad/ sec)

Motor field voltage = Vf= 220volt

For step function :

Initial step = 0.3638 (From PWM calculation)

Final step = 0.3638

For repeating sequence : Frequency = Fc =

1KHz

FOR HYSTERESIS CURRENT CONTROL:

Magnitude of Amplitude = 2

Gain of speed controller Ks= 373.529

For current controller Hc = 1.135294

Speed reference ref= 157 rad / sec

For filter numerated part 0.065 & denominated

part (1+0.01s)



21/58

4. Harmonic Reduction in a Single-Switch, Three-Phase Boost Rectifier

with High Order Harmonic Injected PWM

V. Krishna Murthy, Roll. No. 010611-204 ,M.E (IDC) PTPG V Semester

College Of Engineering, Osmania University.

Abstract

A Traditional three -phase controlled

rectifiers draw non- sinusoidal currents from

the source, the power quality of the

distribution network is greatly deteriorated,

resulting in low efficiency of utilities.

Switching mode rectifiers have gained greater

attention as a good solution, since they draw

perfect sinusoidal currents from the power

distribution network.

Among switching mode rectifiers, a single-

switch three phase boost rectifier is anattractive topology because of its simplicity,

low cost and high efficiency.

In this project, a singleswitch three phase

boost rectifier is studied and simulated.

A single-switch three- phase boost rectifier

cannot be pushed to high power levels due to

high total harmonic distortion (THD).

An approach employing high order harmonic

injected PWM is proposed to meet the IEC

555-2(A) standard for 5-10KW power

application. In this approach, the sixth order Harmonic is

generated and injected to eliminate dominant

5th order Harmonic and also to decrease the

THD.

I. INTRODUCTION:

Basically, two topologies are most popular among

Boost rectifier topologies.

1. A Six-Switch full bridge boost rectifier.

2. A Single-switch boost rectifier.The Single-Switch boost rectifier is shown in fig 1.It

uses six diodes and only one switch to control theinput current and output power.

The phase currents for this rectifier are non-

linear functions of their phase voltages, yielding

several low frequency harmonics.The phase currents

for this rectifier are non-linear functions of their phase

voltages, yielding several low frequencyharmonics.There are two types of switching PWM for

rectifier

Fig 1- A Single Switch Three -Phase Boost Rectifier

1) Variable switching frequency,

2) Constant switching frequency.

In Variable switching frequency the switch is turned on imme

when the rectifier dc-side current falls to zero.However, this

scheme suffers from a serious defect that the fs is load depend

lighter load, the increase of fs results in high switching losses alarge variable fs range complicates inductor design, device selectio

EMI filter design.In this paper, a single-switch rectifier using cons

with harmonic injected PWM (Fig. 2) is presented.

Fig 2- Single-Switch Three-Phase Boost Rectifier With Harmonic Injected PWM

II. HARMONIC REDUCTION WITH

HARMONIC INJECTED PWM

Under balanced and undistorted input phase voltages are:

Va = Vm sin(t)



22/58

Vb = Vm sin(t - 2/3)

(1)

Vc = Vm sin(t - 4/3)

The average input current over the (0, /2) interval in a

single-switch rectifier with constant fs PWM is givenby [3, 6]

ia = Vo T2on sin(t)

(0 t

/6)

2LTsw 3M-3 sin(t)ib = Vo T

2on Msin(t) + sin(2t - 2/3)

2LTsw[3M-3 sin(t + 2/3)][M - sin(t + /6)](/6 t

/3)

ic = Vo T2on Msin(t) + sin(2t + /3)

2LTsw[3M + 3 sin(t + 2/3)][M - sin(t + /6)](/3 t /2)

(2)

Where, Ton = DTsw, D is the duty cycle, Tsw is the

switching period, L is the input inductor and M is the

rectifier voltage gain, which is defined as: M = Vo/Vlp,

where Vo is rectifier output voltage and Vlp is inputline peak voltage.From above equation, the THD and

harmonic contents for different power levels can be

calculated by Fourier analysis.The lower the M, the

higher the current distortion.

In Fig. 4(a), the THD is plotted with respect to M.

It can be seen that in order to meet the THD


23/58


24/58

Fig 9- Frequency Spectra Of The Currents With Harmonic

Injection (m=4.6%)

III.CONCLUSIONS

The proposed approach, sixth order harmonic injected

PWM, simply realizes the injection concept at thecontrol circuit so that the cost of the power stage is

reduced.By using harmonic injected PWM, the THDin a single-switch rectifier is improved, especially for

lower M values.To meet THD


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5. Sensorless Speed Control of Induction Motor Using

Adaptive Technique

Pothana Santhosh1, D.R.Patil21P.G Student, Walchand College of Engg, Sangli (M.S) 416415

2Head of Elec. Dept, Walchand College of Engg, Sangli (M.S) 416415

Abstract

This paper describes a Model Reference

Adaptive System (MRAS) for speed control of the

Induction Motor drive (IM) without a speed sensor. In

this scheme an Adaptive Pseudoreduced-order Flux

Observer (APFO) is used instead of the Adaptive Full-

order Flux Observer (AFFO), an APFO is used for

estimate the IM rotor speed and stator resistance, and

these are used as feedback signals for the FieldOriented Control (FOC), which is a widely used

control method for Induction Motor drive (IM).Simulation results show that the proposed scheme can

estimate the motor speed under various adaptive PI

gains and estimated speed can replace to measured

speed in sensorless induction motor drives, this

scheme is more efficient at very low speed, and also

observed line currents, torque and speed under no-

load and load conditions.

Keywords - Adaptive speed estimation, Induction

Motor, Model reference adaptive control.

1. Introduction

Indirect field-oriented control (IFOC) method is

widely used for IM drives. Within this scheme, a

rotational transducer such as a tachogenerator, an

encoder, was often mounted on the IM shaft. However,

a speed sensor cannot be mounted in some cases, such

as motor drives in a hostile environment. Also such

sensors lower the system reliability and require specialattention to noise. Therefore, sensorless induction

motor (IM) drives are widely used in industry for theirreliability and flexibility, particularly in hostile

environment [5].Various sensorless field-oriented control (FOC)

methods for induction motor (IM) drives have been

proposed using software instead of hardware speed

sensor [1-4, 7]. Adaptive full-order flux observers

(AFFO) for estimating the speed of IM were

developed using Popovs and Lyapunovs stabilitycriteria [1, 3, 7]. While these schemes are not

computationally intensive, an AFFO with a non-zero

gain matrix may become unstable. However,

large speed errors may occur under heavy loads

and steady-state disturbances affecting light

loads. An adaptive pseudoreduced- order flux

observer (APFO) for sensorless FOC wasproposed in using the Lyapunovs method [2].

The performance of the estimator using APFO

was shown to be superior compared to that using

AFFO scheme only at medium speed.

In the MRAS-based technique for sensorlessinduction motor drives the rotor speed is

estimated with an APFO and is used as the

feedback signal for the FOC. The rotor flux isestimated through a closed-loop observer, thus

eliminating the need for auxiliary variables

related to the flux and need for the pure

integration for flux calculations. As a result, the

drive has a wider adjustable speed range and can

be operated at zero and very low speeds.

2. Model Reference Adaptive System

The model reference adaptive system(MRAS) is one of the major approaches for

adaptive control [6]. Among various types of

adaptive system configuration, MRAS isimportant since it leads to relatively easy to

implement systems with high speed of adaptation

for a wide range of applications. The basic

scheme of the MRAS given in Fig. 1 is called a

parallel configuration (output error method)

MRAS in order to differentiate it from other

MRAS configurations where the relative

placement of the reference model and of theadjustable system is not the same. The MRAS

scheme presented above are characterized by the

fact that the reference model was disposed in

parallel with the adjustable system.

The use of parallel MRAS is determined by

its excellent noise-rejection properties that allow

obtaining unbiased parameter estimates, and in

this scheme an error vector is derived using the

difference between the outputs of two dynamic

models, i.e. the reference and adjustable models,where only one of the models includes the



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estimated parameter as a system parameter, i.e.

speed/resistance, and the inputs of two models are the

same. The error vector, e, is driven to zero through an

adaptive law. As a result, the estimated parameter

will converge to its true value X [5, 6]. One of the

most noted advantages of this type of adaptive system

is its high speed of adaptation. The block adjustablemodel has the same structure as the reference one,

but with adjustable parameters instead of the unknown

ones.

Fig 1 Basic configuration of a parallel modelreference adaptive system

The main drawback of this algorithm is its sensitivity

to inaccuracies in the reference model, and difficulties

of designing the adaptation mechanism block in

MRAS. Selection of adaptive mechanism gains is a

compromise between achieving a high speed of

response and high robustness to noise and disturbancesaffecting the system. With the large PI gains for rotor

speed identification in adaptive mechanism,the convergence speed for speed estimation is fast;

however, high order harmonic components and noises

are present in the estimated speed.

3. Adaptive Flux Observer

For an induction motor, if the stator current and

rotor flux are selected as the state variables, the

state equations can be expressed as eq.(1) in the

stationary reference frame [1].

Where

Where R1, R2, and L1, L2 are stator and rotorresistances and self-inductances, respectively, Lmis mutual inductance, is the rotor time constant

is electrical motor angular speed.

The APFO flux observer can be written as

follows

Where is and vs are measured values of stator

current vector and stator voltage vector,

respectively, G is the reduced-order observer

gain matrix which is also determined to make eq.

(3) stable and ^ denotes the estimated values.

The observer is a closed-loop system, which is

obtained by driving the estimated model of the

induction motor by the residual of the current

measurement ( .

The estimation of stator currents is conducted

by a closed-loop observer with a

feedback gain matrix G, as in eq. (3), whereasthe estimation of rotor fluxes is carried out by an

open-loop observer of eq.(4) without the flux

error. Therefore, the real and estimated rotor

fluxes are assumed the same.

The observer gain matrix is chosen as:

Where the observer gain matrix G is

calculated based on the pole placementtechnique.

Let us choose,

Where g1 is proportional to the IM

parameters, g2 is an arbitrary gain, k is an



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Fig 3 Block diagram of sensorless IM drive

The current controlled voltage source inverter with

field orientation control provides a fast time response

and a smoother inverter current output. Although

many current control algorithms have been proposed

in recent years, hysteresis band current control is still a

preferred method. This algorithm is especially suitable

for implementing the field orientation control. As a

result, this control algorithm offers a higher quality

dynamical torque control. Estimated rotor speed

and estimated rotor flux angle are achieved by the

MRAS-based pseudoreduced- order flux observer.

And are the magnetizing and torque components of

the stator current, respectively. These components are

the equivalent dc values in the synchronously rotating

reference frame. By the application of inverse Clarke

and Park transformations in Vector Rotator block,

the command values and can be obtained.

These real time values will be compared with the

measured or sensed currents to generate

proper pulsing sequence in order to fire the IGBT

switching devices of the inverter.

Figs. 46 show the behavior of IM speed

estimation under various values of adaptive scheme PI

gains. These figures show that with the large PI gains

for the adaptive scheme, Kp3 and Ki3, the convergence

for the speed estimation is fast; however, a lot of highorder harmonics are present in the estimated speed. In

Fig. 4 where the IM rotates at a constant speed (200

rpm) under no load condition and initial value of the

estimated speed is zero, the estimated speed reaches

the real one in less than 0.5 s. With larger PI gains the

convergence time reduces to 0.2s as in Fig. 5. By

increasing the PI gains for adaptive scheme this

converging time reduces (to less than 0.15 s), however,the estimated speed shows high overshoots as shown

in Fig. 6. Fig. 7 shows the real, command and

estimated rotor flux. When two speeds converge each

other at 0.4 s the estimated flux also converge to

real flux at the same time.

Fig 4 Behaviour of speed estimation at Kp3=4,Ki3=150

In these simulations the real speed is using as

the feedback signal for the PI controller, and then

the speed estimator starts at some time after thereal speed is at steady-state condition. In

simulation there is no noise component in the

real currents and voltages. Therefore the

estimated speed does not have high order

harmonic components and noises in larger PI

gains of speed identifier. In all above simulations

the estimation process of speed starts after 0.15 s.

Fig 5 Behaviour of speed estimation at kp3=5,

ki3=250



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Fig 6 Behaviour of speed estimation at kp3=8,

ki3=350

For investigating of the MRASs behavior under

loading condition a load of 0.5 pu is applied to the IM

at time 0.5 s. Fig. 8 shows that after a small speed drop

both estimated and real speeds converge very well.

Meanwhile this simulation indicates that both speeds

follow reference one with negligible error. ThisSimulation results gives better performance in both the

cases i.e. under no-load and load condition, which are

shown below.

Fig 7 Behaviour of speed estimation at kp3=5,ki3=250

Fig 8 Speed estimation under loading condition

Case 1: Under No-load condition (Reference

speed = 100 rad/sec)

Fig 9 Actual Speed and Estimated speed Using

MRAS in rad/sec



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Fig 10 (a) Line currents in Amps (b) Speed inrad/sec (c) Torque in N-m on no load

Case 2: Step Change in Load

(Reference speed = 100 rad/sec; Load torque of 15 N-

m is applied at t = 0.25 sec.)

Fig 11 (a) Line currents in Amps (b) Speed in

rad/sec (c) Torque in N-m on step change inload

Case 3: Speed Reversal Command

(Reference speed = 100 rad/sec; speed reversal

command is applied at t = 0.5 sec.)

Fig 12 (a) Line currents in Amps (b) Speed in

rad/sec (c) Torque in N-m on no load, speed

reversal

Fig 9 Shows that the actual speed of

induction motor and estimated speed using

MRAS are same, Fig 10 Shows the no load line

currents, speed and torque wave forms, it can be

seen that at starting the values of currents and

torque will be high. The motor reaches to its

final steady state position within 0.2 sec. Hence

it has fast dynamic response; Fig.11 shows theline currents, speed and torque wave forms under

load condition. First the motor is started under no

load and at t = 0.25 sec a load of 15 N-m is

applied. It can see that at 0.25 sec, the values of

currents & torque will increase to meet the load

demand and at the same time speed of motor is

slightly falls.

The motor is started under no load conditionand speed reversal command is applied at t = 0.5

sec. At 0.5 sec the motor speed decays from 100

rad/sec and within 0.1 sec it reached its final

steady state in the opposite direction. At 0.5 sec

torque will increase negatively and reaches tosteady state position corresponds to steady state

speed value.

6. ConclusionThis paper presents a MRAS-based APFO

sensorless induction motor drive. This method

has been applied to a direct field-oriented

induction motor control with and without speed



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sensors. The simulation results demonstrated that, with

larger PI gains for the adaptive PI regulators, the

convergence for the speed estimation is fast, however,

higher order harmonics and noises are included in the

estimated speed. The validity of the MRAS-basedpseudoreduced-order flux observer has been verified

by simulation.

7. REFERENCES

[1]. H. Kubota, K. Matsuse, and T. Nakano, Dsp-Based Speed Adaptive Flux Observer of Induction

motor, IEEE Trans. Ind. Appl. 29 (1993) 344348.

[2] Y.N. Lin, and C.L. Chen, Adaptive

pseudoreduced-order flux observer for speed

sensorless field oriented control of IM, IEEE Trans.

Ind. Electron. 46 (5) (1999) 10421045.

[3]. G. Yang, and T.H. Chin, Adaptive-speedidentification scheme for a vector-controlled speedsensorless inverter-induction motor drive,IEEE

Trans. Ind. Appl. 29 (4) (1993) 820825. Fig 12

Sensorless IM drive, (a) measured speed, (b) estimated

speed. H.M. Kojabadi /Simulation Modelling Practice

and Theory 13 (2005) 451464 463

[4] C. Schauder, Adaptive speed identification for

vector control of induction motors without RotationalTransducers, IEEE Trans. Ind. Appl. 28 (5) (1992)

10541061.

[5] H.M. Kojabadi, L. Chang, Model reference

adaptive system pseudoreduced-order flux observer for

very low speed and zero speed estimation in sensorless

induction motor drives, in:IEEE Annual Power

Electronics Specialists Conference, Australia, vol. 1,2002, pp.

[6] Y.D. Landau,Adaptive Control -The Model

Reference Approach, Marcel Dekker, New York,

1979.

7]. J. Maes, J.A. Melkebeek, Speed-sensorless direct

torque control of induction motor using an adaptiveflux observer , IEEE Trans. Ind. Appl. 36 (3) (2000)

778785.

[8]. I.D. Landau, Elimination of the real

positivity condition in the design of parallel

MRAS , IEEE Trans. Automat Contr. 23 (6)

(1978) 10151020



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6. Modeling and Simulation of High Efficiency DCDC Converter for an

Auxiliary Power Unit

GVSSNS Sarma, Assistant Professor, Centre for Energy Research, EEE Dept., Auroras EngineeringCollege, Bhongir, A.P.

E-mail :[email protected]

Abstract

The simulation study of high efficiency DC-

DC boost converter for an auxiliary converter

is presented in this paper. The main advantageof this converter is based on the energy

recovery system. The proposed converter

does not consider the leakage inductance ofthe transformer as a parasite and uses it for

energy transfer, thus avoiding problems oflow efficiency and waveform distortions and

also voltage instability caused by leakageinductance. Apart from these advantages the

proposed converter has another few features

like elimination of separate filter inductor andproduction of soft starting by using the power

electronic switches.

Index TermsAPU, DC-DC converter, fuel cell, solar

cell.

I. INTRODUCTION

This high DC DC boost converter is

proposed to use in an Auxiliary Power Unit(APU). The block diagram of APU is shown

in figure 1. The Auxiliary Power Unit acts as

a back up for the utility under the absence of

mains supply. The main functional

components of this APU is a solar panel/fuelcell, DC-DC converter and an inverter with

230V and 50Hz output.In order to get anoutput of 230V from the inverter, we require

at least 350 volts DC supply. This high DC

source can not be sourced in the remoteapplications. So it needs a booster for

boosting a voltage of (20-30)V obtained from

the solar cells / fuel cells.This boosting can also bedone by using an ordinary boost converters which

suffers from lowered efficiency due to high duty

ratio maintained for obtained high dc voltage as anoutput. As per the experimental data the average

efficiency of these converters will be approximately

40% to 50% only.

Then, even one can go for push pull or full bridge

converters configurations to overcome tproblems but again the large turns ratio maintained

in the booster transformers offers very high leakage

reactance. This leakage reactance effect aproduces low efficiency due to reactive power

consumption and also waveform distortion

finally voltage instability even though

controllers are used.

Fig. 1. Typical layout of APU.

Fig. 2. Topology of the proposed dcdc converter.

so to overcome the problems highlighted in all

the above said converters, the new DC-DCconverter is proposed. This converter can yield

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an overall efficiency of about 90% and

cost will be reduced as some of the filter

components can be eliminated. Thetransformer is operated at high frequency

so the cost as well as size of the

transformer can be reduced. So alltogether the proposed converter has high

efficiency, economical and compatible.

II. PROPOSED DCDC CONVERTER

A. Topology

Fig. 2 shows the topology of the proposedconverter, where FC is the low voltage

fuel cell, S1-S6 are active switches, D1-

D6 are body diodes of switches S1-S6,

respectively, D7 and D8 are powerdiodes, Cis the filter capacitor, Tis the

transformer, and R is the load of the dc-

dc converter.

Fig.3. Transformer primary side referred equivalentcircuits of the converter during different time periods

in the first half cycle: (a) t0t1, (b) t1t2, (c) t2-t3, and

(d) t3-t4.

B. Operation

The transformer primary side referred equivalent

circuits of the converter are shown in Fig. 3and are

used to explain the operation of the converter. Themagnetizing inductance of the transformer is ignored

and only the leakage inductance is considered in the

derivation of the equivalent circuits. The waveformsof key components of the converter in one complete

cycle are shown in Fig. 4.

In Figs. 3 and4, VI, Vor, Vp, Vsr, VL, and IL stand

for the input voltage of the converter, output voltage

of the converter (primary side referred), primary sidevoltage of the transformer, secondary side voltage of

the transformer (primary side referred), vo

across the leakage inductance of the transformer(primary side referred), and primary side current of

the transformer, respectively.

In Fig. 4, G1-G6 represent the gating signals toswitches S1-S6, respectively, and the time periodfrom t0t8 represents a complete operating cycle of

the converter. As shown in Fig. 4, the operation of

the converter in the second half cycle, from t4-t8, is

similar to that in the first half cycle, from t0-t4,except being in the opposite direction. Therefore,

only the operation of the converter in the first half

cycle, from t0-t4, is detailed and illustrated in Fig.3(a)-(d).

The operation of the converter during different time

periods in the first half cycle is expla

follows.

[t0-t1]: Switches S2, S3, and S5 are gated. A closed

current path is created as shown in Fig. 3(a). Onecan easily derive that Vp = Vi, Vsr= 0 and

VL = (Vp - VSr) = (Vi - 0) = Vi



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Using VL= Vi and VL = L(dlL/dt), whereL is the leakage inductance of the

transformer, one can derive

.tL

ViIL = Eqn.(1)

It should be noted that S2, S3, and S5 areturned on at zero current condition

[t1-t2]: Switches S2 and S3 are kept on

while switch S5 is turned off. D7 conducts

to carry the inductor current as a result of

the turn-off of S5. A closed current path iscreated as shown inFig. 3(b). One can

derive that Vp = Vi, Vsr= Vor and VL= Vp

- Vsr= Vi Vor. Similar to Eqn. (1), onecan have

12 TTL It

L

VorViII +

== Eqn.(2)

where IT1 is the current through the

tansformer at time instant t1, and can be

calculated using (1). As a result, the current in

the transformer continues to rise

linearly, but now at a slower rate, as

is shown in Fig. (4).

[t2-t3]: Switch S2 is turned off while

S3 is kept on. D4 conducts to carry

the inductor current as a result of theturn-off of S2. The inductor current

flows as shown in Fig 3(c) and is

given as

tL

VorII TL = 2

Eqn.

(3)

where IT2 is the current through the

transformer at time instant t2, and

can be calculated using Eqn.(2).

[t3-t4]: No current or energy flow inthe converter. S3 is turned off at t=t4. It should be noted that S3 is

turned off at zero current condition.

The proposed converter is operated ata fixed switching frequency. As can

be seen from the description of the working of the

converter, time periods T1 and T2 control

current through the transformer and hence the powerof the converter. It can also be seen that switches S5

and S6 are turned on for time period T1, with a 180

phase difference. Switches S1 and S2 are turned onfor a time period equal to T1 + T2, with a 180 phase

difference. And switches S3 and S4 are turned on for

half of the switching time period (T/2), with a 180phase difference.

C. Control

The control strategy of the proposed converter is

shown in Fig. 5. The output voltage of the converter

is sensed and compared to the reference voltage(VOref). The voltage error thus obtained is passed

through a proportional-integral (PI) controller toobtain the reference output current (IOref). Theoutput current Io is sensed and compared to the

Ioref. The current error thus obtained is passed

through two different PI circuits. The signals thus

obtained are compared to a high frequency (equal toswitching frequency) saw tooth signal to generate

pulse-width modulated (PWM) control signals with

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Fig. 4. Waveforms of key components of the converter in one complete cycle.

168


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pulse widths T1 and T1+ T2. A constant

value signal is also compared to the same

saw tooth signal to generate PWM controlsignal with pulse width T/2. These three

PWM control signals of pulse width T1, T1 +

T2, and T/2 are individually phase delayedby 180 to obtain three more PWM control

signals.

Thus a total of six PWM control signals are

obtained which are used to control the sixactive switches of the proposed converter, as

indicated in Fig. 5.

III. SIMULATION RESULTS

Performance of the proposed converter is

simulated on a open loop for a fixedoperating point of 20Volts input voltage and

an output voltage 250Volts DC.

The simulation results are shown in Fig. 6

where from top to bottom is primary sidevoltage(Vp), secondary side vo

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