«modeling and control of an electric vehicle combining bond graph …€¦ · emr’13 lille sept....

EMR’13

Lille

Sept. 2013

Summer School EMR’13“Energetic Macroscopic Representation”

««MODELING AND CONTROL OF AN MODELING AND CONTROL OF AN

ELECTRIC VEHICLE COMBINING BOND ELECTRIC VEHICLE COMBINING BOND

GRAPH AND EMRGRAPH AND EMR»»

Dr. Luis SILVA

GEA, Univ. Nac. de Rio Cuarto, Argentina

[email protected]

UNIVERSIDAD UNIVERSIDAD NACIONAL DE NACIONAL DE RRÍÍO CUARTOO CUARTO

Prof. Alain BOUSCAYROL

L2EP, University Lille1, MEGEVH network,

[email protected]

- Presentation Outline -

EMR’13, Lille, Sept. 2013

““Modeling and Control of EV Combining BG and EMRModeling and Control of EV Combining BG and EMR””

Introduction

Bond Graph and EMR of the Electric Vehicle

Development of the Control Structure

Simulation Results

Conclusions

2

2/16



3- Introduction -

Simulation is crucial before manufacturing.

Model can be represented with functional/structural approach.

Introduction 3/16



4- Introduction -

EV model using BGEV model using BG

Simulation is crucial before manufacturing.

Model can be represented with functional/structural approach.

ObjectiveObjective

New simulation environment

where both

approaches can

coexist

Introduction

EV model using EMREV model using EMR

FunctionalFunctional

Systems represented by relations between inputs/outputs.

Connections between sub-systems are virtual links.

Analysis of global performance and design its control.

StructuralStructural

Links respond to physical connection based on the topology.

Direct correspondence between system and representation.

Useful for system design and its analysis in faulty conditions.

4/16

EMR’13

Lille

Sept. 2013

Summer School EMR’13“Energetic Macroscopic Representation”

««BOND GRAPH AND EMR OF THE BOND GRAPH AND EMR OF THE

ELECTRIC VEHICLEELECTRIC VEHICLE »»

BG and EMR of the EV



6- Bond Graph and EMR of the Electric Vehicle -

6/16




To keep the integral causality, conflicts of association

(when two different accumulative elements try to impose

the same state variable) are solved using the permutation

and merging rules. First the accumulative elements in

conflict are "moved" together (permutation) and then it is

generated an equivalent accumulative element (merging).

7/16




Control Structure

Tuning path

8/16




Control Structure

Control path

9/16




Control Structure

(24)

(25)

(26)

(23)

(20)

(21)

(22)

(19)

(18)

10/16



11- Simulation Results -

Simulation Results 11/16



12- Simulation Results -

Simulation Results

1) Straight Line Motion 2) Turning Maneuver

a) vehicle velocity. b) Modulating signal.

Armature current evolution.

Steering angle of frontal wheels.

Angular velocities of both wheels.

12/16



13- Conclusions and Further Work -

Conclusions

CONCLUSIONS

EMR is not frozen

The proposal allows exploiting the advantages of each approach

Representing the system in BG (faults) and the control with EMR

The idea can be extended to any complex and large scale physical system

CONCLUSIONSCONCLUSIONS

EMR is not frozen

The proposal allows exploiting the advantages of each approach

Representing the system in BG (faults) and the control with EMR

The idea can be extended to any complex and large scale physical system

13/16



14- Conclusions and Further Work -

Conclusions 14/16

Validation using experimental resultsValidation using experimental resultsProposed model to evaluate the Proposed model to evaluate the

close loop performanceclose loop performance



15- Biographies and References -

Dr. Luis SILVAUniversidad Nacional de Rio Cuarto, GEA, Argentina

University Lille 1, L2EP, France

PhD in Sciences of Engineering at UNRC (2012)

Research topics: EMR, Modeling and Simulation of Electric and Hybrid Vehicles

UNIVERSIDAD UNIVERSIDAD NACIONAL DE NACIONAL DE RRÍÍO CUARTOO CUARTO

Prof. Alain BOUSCAYROLUniversity Lille 1, L2EP, MEGEVH, France

Coordinator of MEGEVH, French network on HEVs

PhD in Electrical Engineering at University of Toulouse (1995)

Research topics: EMR, HIL simulation, tractions systems, EVs and HEVs



16- Biographies and References -

[1] L. I. Silva, A. Bouscayrol, C. H. De Angelo and B. Lemaire-Semail, "Coupling Bond Graph and Energetic Macroscopic Representation for Electric Vehicle Simulation". International Journal of Mechatronics, Submitted April 2013.

[2] Chan, C., Bouscayrol, A., Chen, K. "Electric, hybrid, and fuel-cell vehicles: Architectures and modeling". Vehicular Technology, IEEE Transactions on 2010; 59(2) 589-598.

[3] Silva, L.I., de la Barrera, P.M., De Angelo, C.H., Aguilera, F., Garcia, G. "Multi-domain model for electric traction drives using bond graphs". Journal of Power Electronics 2011; 11(4) 439-448.

[4] Bouscayrol, A., Pietrzak-David, M., Delarue, P., Pena-Eguiluz, R., Vidal, P.E., Kestelyn, X. "Weighted control of traction drives with parallel-connected AC machines". Industrial Electronics, IEEE Transactions on 2006; 53(6) 1799-1806.

[5] Delarue, P., Bouscayrol, A., Barrade, P. "Energetic macroscopic representation and PSIMR simulation: Application to a DC/DC converter input flter stability". In VPPC 2010.

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