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EMR’16

UdeS - Longueuil

June 2016

Summer School EMR’16

“Energetic Macroscopic Representation”

« EMR AND INVERSION-BASED CONTROL

OF AN ELECTRIC VEHICLE »

Prof. João P. Trovão1, Dr. W. Lhomme2

1 e-TESC, Université de Sherbrooke, Canada2 L2EP, Université Lille1, France

http://www.emrwebsite.org/

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« EMR and IBC of an Electric Vehicle »

EMR’16, UdeS Longueuil, June 2016

- Introduction -

model representation simulation

Simulation is a key issue before working on a real system…

Tazzari Zero

of L2EP

real

system

i mi

V mu

dcmchopchop

batchopchop

dcmarmdcmchopdcmarm iReuidt

dL

geardcmdcm

dcmdcmdcm

ke

ikT

geargeardcmgear fTTdt

dJ

diffgeargear

dcmgeargear

k

TkT

whdifdif

geardifdif

k

TkT

restotev FFvdt

dM

How to organize simulation? Control?

2

3



- Outline -

1. Studied EV

2. EMR of the studied EV

3. Inversion-based control of the EV

EMR’16

UdeS - Longueuil

June 2016



« STUDIED ELECTRIC VEHICLE »

3

5



- Tazzari Zero EV -

ubat iim2

1 2 3

Tim

gear iim1

its

itot1

Tazzari Zero characteristics

• 15 kW induction machine

• 80V 160Ah LiFePO4 battery

• 542 kg (empty mass)

• Maximum speed: 85km/h

6



- Simplified EV -

Objective:

control of the traction system in straight lines

Simplifications:

• a permanent magnet DC machine is considered in a first step

• an equivalent wheel is considered (no curve)

ubat

i T im

gear

its

4

EMR’16

UdeS - Longueuil

June 2016



« EMR OF THE

STUDIED ELECTRIC VEHICLE »

8



- EMR of the EV -

ubat

T im

gear

its

ubat

ichop

uchop

iarm

mchop

i

u

chopchop

chopchop

arm

bat

im

Vm

Battery

Structural

Representation

Functional Description

5

9



idcm

- EMR of the EV -

ubat

i

T im

gear

its

ubat

Battery

ichop

uchop

iarm

Tdcm

shaftedcm

mchop

gear

Tgear

dcmarmdcmchopdcmarm iReuidt

dL geargeardcmgear fTT

dt

dJ

geardcmdcm

dcmdcmdcm

ke

ikT

10



- EMR of the EV -

ubat

i

T im

gear

its

ubat

Battery

ichop

uchop

iarm

Tdcm

shaftTwh

idcm

Tdiffedcm

mchop

Fwh

shaft

Tgear

gear diff vev

shaftgeargear

diffgeargear

k

TkT

geardifdif

whdifdif

k

TkT

diffwhev

whwhwh

Rv

FRT

6

11



- EMR of the EV -

ubat

i

T im

gear

its

ubat

Battery

ichop

uchop

iarm

Tdcm

shaftTwh

idcm

Tdiffedcm

mchop

FwhTgear

gear diff vev Fwh

Fres

vev

vev

restotev FFvdt

dM

shaft

12



shaft

- EMR of the EV -

ubat

i

T im

gear

its

ubat

Battery

ichop

uchop

iarm

Tdcm

shaftTwh

idcm

Tdiffedcm

mchop

FwhTgear

gear diff vev Fwh

Fres

vev

vev

Conflict of association:

shaft and vev state variables but shaftgeardiffwhev kkRv

permutations

7

13



- EMR of the EV -

ubat

i

T im

gear

its

ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Fwh

Fres

vev

vev

Conflict of association:

a unique state variable is required!

merging

Tgear Tdiff vev

restoteveq FFvdt

dM

222

whdiffgear

shaft

eqRkk

JMM

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- EMR of the EV -

ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.

a

A

aM g

Faero

½ Froll½ Froll

Fgrade

aa sinMgvACcosMgkF evxairrollres 2

2

1

8

EMR’16

UdeS - Longueuil

June 2016



« INVERSION-BASED CONTROL OF THE

STUDIED ELECTRIC VEHICLE »

16



- Tuning path -

Objective: control the EV velocity

Tuning variable: modulation ratio of the DC-DC converter

chopper DC machine gearboxes wheel chassis

ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.

9

17



- Maximum Control Structure -

Maximum Control Structure:

• inversion of each element step-by-step

• all variables are assume measurable


ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.

vev-refFwh-refTdiff-refTgear-refTdcm-refidcm-refuchop-ref

18



- Inversion of chassis -





ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.


vev_ref

C(s)Fwh_ref

vev_mea

+-

Fres_mea

++

vevFtran

-

Fres

+s

M/1

vev

10

19



- Inversion of wheel -





ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.

vev-refFwh-refTdiff-refTgear-refTdcm-refidcm-refuchop-refTdiff-ref Fwh-ref

TdiffFwh

Ωdiff

whR

1

whR

vev

whR

1

20



- Practical Control Structure -

Example of simplification:

• merging of gains


ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.


merging

ktot=k1k2k3k4

11

21



- Practical Control Structure -

Example of estimation:

• estimation of velocity


ubat

Battery

ichop

uchop

iarm

Tdcm

shaft

idcm

edcm

mchop

Fwh

Fres gear diff vev

Tgear Tdiff vev

Env.


vev-est

22



- Simulation -

Matlab-Simulink ©, using the EMR library

12

23



- Implementation on the real vehicle -

Electronic

Control Unit

sensors

EMR’16

UdeS - Longueuil

June 2016



« REFERENCES »

13



- References -

A. Bouscayrol, W. Lhomme, P. Delarue, B. Lemaire-Semail, S. Aksas, “Hardware-In-the-Loop simulation of

electric vehicle traction systems using Energetic Macroscopic Representation”, IEEE-IECON'06, Paris,

November 2006.

A. Bouscayrol, A. Bruyère, P. Delarue, F. Giraud, B. Lemaire-Semail, Y. Le Menach, W. Lhomme, F. Locment,

“Teaching drive control using Energetic Macroscopic Representation - initiation level”, EPE'07, Aalborg,

September 2007.

K. Chen, P. Delarue, A. Bouscayrol, R. Trigui, “Influence of control design on energetic performances of an

electric vehicle”, IEEE-VPPC'07, Arlington (U.S.A.), September 2007.

K. Chen, A. Bouscayrol, W. Lhomme, “EMR and Inversion-based control: application to an Electric Vehicle

with an electrical differential”, Journal of Asian Electric Vehicles, vol. 6, no.1, p. 1097-1102, June 2008.

J. P. Trovao, M. R. Dubois, M. A. Roux, E. Menard and A. Desrochers, “Battery and SuperCapacitor

Hybridization for a Pure Electric Three-Wheel Roadster”, IEEE-VPPC‘15, Montreal, QC, October 2015.

C. Depature, W. Lhomme, A. Bouscayrol, “Teaching Electric Vehicle drive control using Energetic

Macroscopic Representation”, EVS’27, Barcelona (Spain), November 2013.

W. Lhomme, Ph. Delarue, Ph. Barrade, A. Bouscayrol, “Maximum Control Structure of a series hybrid electric

vehicle using supercapacitors”, EVS'21, Monaco, April 2005.



« BIOGRAPHIES »

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- Authors -

Prof. João P. Trovão

Université de Sherbrooke, e-TESC Lab., Qc, Canada

PhD in Electrical Engineering at University of Coimbra (2012)

Research topics: Electric Vehicles, Multiple Energy Storage,

Energy Management

Dr. Walter LHOMME

University Lille 1, L2EP, MEGEVH, France

PhD in Electrical Engineering at University of Lille1 (2007)

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

Energy Storage Subsystem, Traction subsystems,

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