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EMR’17

Lille

June 2017

Summer School EMR’17

“Energetic Macroscopic Representation”

« ENERGETIC MACROSCOPIC

REPRESENTATION (EMR) »

Prof. Alain BOUSCAYROL1, Prof. Philippe BARRADE, 1 L2EP, Université Lille1, MEGEVH network, France2 University of Applied Sciences of Sion, Switzerland

Within the DL program of IEEE-VTS

2

« Energetic Macroscopic Representation (EMR) »

EMR’17, Lille, June 2017

- Outline -

1. EMR basic elements

• Source, accumulation and conversion elements

• Coupling and adaptation elements

2. Association rules

• Permutation rule

• Merging rule

2. EMR of a complete system

• Action and tuning path

3. Conclusion

3



real

system

system

model

system

representation

- Level of study -

system

simulation

model

objective

limited

validity range

organization

valuable

properties

behavior

study

prediction

4



- Representation main goal -

• The graphical description is chosen depending on objectives

– real-time control and energy management of energetic systems

systemic

(cognitive)

causal models

functional

descriptionstatic or

quasi-static

modelscausal

dynamical models

& forward

approach

EMR’17

Lille

June 2017



1. « EMR basic elements »

6



- The different elements -

Energy sources

Energy storage

Energy conversion

Energy distribution

Only 4 energy functions

are required to describe

energy conversion systems

EMR = 4 graphical elements associated with the 4 energy functions

7



Sourceoval pictogram

background: light green

contour: dark green

1 input vector (dim n)

1 output vector (dim n)

- Energetic sources -

terminal elements which represent

the environment of the studied system

generator and/or receptor of energy

power system

reaction

action

upstream

source

downstream

sourcex1

y1

x2

y2

p1= x1. y1 p2= x2. y2

direction of

positive power

(convention)

n

i

ii yx

1

11

8



pload

qwind

wind

qwind [m3/s]

Pload [Pa]

bulbI

u

I

u

Wind

(air flow source)

generator energy

VDC

iBat

VDC

i

- Energetic sources: examples -

Battery

(voltage source)

generator and

receptor of energy

Ligthing bulb

receptor of energy

IC engine

(torque source)

generator

of energyTice

WICE

Tice

W

Tice-ref

9



Accumulatorrectangle with an oblique bar

background: orange

contour: red

upstream I/O vectors (dim n)

downstream I/O vectors (dim n)

- Accumulation elements -

internal accumulation of

energy (with or without

losses)

reaction

actionx1

y

y

x2

p1= x1. y p2= x2. y

causality principle

output(s) = input(s)

dtxxfy ),( 21

y = output, delayed with

regard to input changes

fixed I/O (causal description)

10



inductor

v1

v2

i

i

v1 v2

i

L

v

i2i1

C

capacitor

i1

i2

v

v

inertia

WJ

T2T1

W

T1

T2

W

W

stiffness

kW1 W2

TT

W1

W2

T

T

2 2

1iLE

2 2

1W JE

2 1

2

1T

kE

2 2

1vCE

- Accumulation elements: examples -

11



conversion

elementvarious pictograms

background: orange

contour: red

upstream I/O vectors (dim n)

downstream I/O vectors (dim p)

Possible tuning input vector (dim q)

- Conversion elements -

conversion of energy

without energy

accumulation

(with or without

losses)

action /

reaction x1

y1

y2

x2

p1= x1. y1 p2= x2. y2

),(

),(

21

12

zxfy

zxfy

z

tuning vector

no delay!

upstream and downstream

I/O can be permuted

(floating I/O)

12



kF

- Conversion elements: examples -

dcmdcmdcm euiridt

dL

VDCuconv

iloadiconv

VDC

iconv

uconv

s

iload

s

i

u DCM

Wgear

TgearT1

W2

W2

T3

kgear

3gear2 TTdt

dJ W

WF

F

ke

ikT

dcm

dcmdcm

idcm

u idcm

edcm

Tdcm

W

Wgear

T1

W2

Tgear

W2

T3

2geargear

1geargear

k

TkT

WW

m

loadconv

DCconv

imi

Vmu

Bat

13



coupling element

various overlapped pictograms

background: orange

contour: red

pairs of I/O vectors

N pairs, N-1 pictograms

- coupling elements -

distribution of energy

without energy

accumulation

without tuning

(with or without

losses)

action /

reaction x1

y1

p1= x1. y1

)x,..x(fy

...

)x,..x(fy

nnn

n

1

111no delay!

x2

xn

yn

y2

14



- Coupling elements: examples -

2

TTT

gearrdifldif

iarm

uarmDCM

iexc

uexc

Wexcdcm

armexcdcm

ike

iikT iarm

uarm

iexc

uexc

iarm

earm

Tdcm

W

eexc

iexc

Field winding DC machine

Mechanical differential

Wdiff

Tgear

Wlwh

Wrwh

Tldiff

Trdiff

Tldiff

Wrwh

Trdiff

Wlwh

Tgear

Wdiff2

ΩΩΩ rwhlwh

diff

15



- EMR main properties -

Energy

source

Energy

accumulation

Energy

conversion

(potential tuning)

Energy

distribution

highlight energetic functions

all power I/O are defined

by accumulation elements

(causality)

only conversion elements

can have tuning inputs

all elements are connected

by action/ reaction (power link)

(systemic)

valuable for control design

EMR’17

Lille

June 2017



3. « Association Rules »

17



Association rules: conflicts of association

• Systemic: Science for the study of systems, and their interaction

– Considering S1 and S2 any kind of sub-systems

• The direct connection of S1 and S2 is only possible if

out(S1) = in(s2)

in(S1) = out(S2)

Bat

VDC

iL

u

VDC VDC

iLiL

iL

u

L iL

VDC

iL

iL

u

Bat

uVidt

dL DCL

i state variable

Example

OKy2

x2x2

y2y1

x1 x3

y3

18



Association rules: direct connection

• Example: two inertia linked by a fix ratio gearbox

• Models

• Representation

W1W1

T2

T3

W2

T1

T4

W2J1

J2

W1

W1

T2

T1

J1 W2

T3 W2

W2

T4

T3

J2

k

W1

T2

causal causalnon causal

19




• Example: two inertia linked by a fix ratio gearbox

– Direct connection 1:

– Direct connection 2:

• Use the property of a non causal element to permute inputs and outputs

• Still conflict of association

W1

W1

T2

T1

J1 W2

T3 W2

W2

T4

T3

J2

k

Conflict of association

W1

W1

T2

T1

J1

W2

T3

W2

W2

T4

T3

J2

1/kW1

T2

W1

W1

T2

T1

J1

W2

T3 W2

T4

J2

kW1

T2

20




• Remain

– The property of a non causal element to permute inputs and outputs can be

efficiently used

• I/Os of a non causal element are fixed by state variables (accumulation element), does not

necessarily solve conflicts of associations

• In case conflicts of association subsist

– Back to the model

T'2 =T1

Kwith

W2

T’2 W2

T3

J1/K2

1/kW1

T1

W2

W2

T4

T3

J2

Conflict of association

2 accumulation elements

would impose the same

state variable x1

21




• Remain

– Permutation of elements is possible if one obtain the same global behavior:

• strictly the same effects (y1 and x3) from the same causes (x1 , y3 and z)

x2

y2y1

x1 x3

y3

x’2

y’2y1

x1 x3

y3

z zx2

y2y1

x1 x3

y3

z

Permutation Rule

22




• Remain

– The property of a non causal element to permute inputs and outputs can be

efficiently used

– Permutation rule

• In case conflicts of association subsist

– Back to the model

T'2 =T1

Kwith

W2

T’2 W2

T3

J1/K2+J2

1/kW1

T1

One has finally merged 2 accumulation elements series connected

(same state variable)

23




• Remain

– When 2 accumulation elements impose the same state variable

• Conflict association

• Solution: Merging rule

Merging Rule

x1

x1y2

y2

x1

y1 x1

y3

NO

merging x1

y3x1

y1

1 equivalent function for

2 elements / systemic

EMR’17

Lille

June 2017



3. « EMR of a complete system »

Prof. Alain BOUSCAYROL, Dr. Walter LHOMME

(University Lille1, L2EP)

25



- Example: a lift -

Assumptions:

- ideal switches

- DC Machine not saturated

W

TmLs, rs

uch

um

ich

VDC

im

shaft pulleyDCMchoppersupply

counter

weight

cage

Tpul

vcage

filter

uc

iLLf, rf

CW

inductor

Technical requirement:

- control of velocity vcage

- tuning input = modulation ratio of chopper m

26



- Lift example: EMR -

W

TmLs, rs

uch

um

ich

VDC

im

inductor shaft pulleyDCMchoppersupply

counter

weight

cage

Tpul

vcage

filter

uc

iLLf, rf

CW

mmerging

permutation

and merging

VDC iL

iL uC

Bat Env

ich

uC

im

uch

em

im

W

Tm Fpul

vcage

vcage

Fres

filter chopper DC machine pulley cage+CW

27



P >0 P<0

- Lift example: tuning path -

W

TmLs, rs

uch

um

ich

VDC

im

inductor shaft pulleyDCMchoppersupply

counter

weight

cage

Tpul

vcage

filter

uc

iLLf, rf

CW

tuning path

VDC iL

iL uC

Bat Env

ich

uC

im

uch

em

im

W

Tm Fpul

vcage

vcage

Fres

filter chopper DC machine pulley cage+CW

m

28



x1

x1y2

y2

- EMR and systemic -

I/O are independent

of power flows

Tuning paths:

• defined by the technical requirements

• independent of the power flow direction

EMR describes energetic

functions

EMR is adapted for control design

x1

y1 x1

y3

x1

y2 x1

y3

Priority to the function

by keeping the physical causality

(systemic)

EMR’17

Lille

June 2017


“Energetic Macroscopic Representation”« Conclusion »

EMR = multi-physical graphical description

based on the interaction principle (systemic)

and the causality principle (energy)

Basic elements = energetic function

sources, accumulation, conversion and distribution of energy

Association rules = holistic property of systemic

enable keeping physical causality in conflict of association

Applications

analysis, simulation, control organisation…

30



- Speaker & contributors -

Prof. Alain BOUSCAYROL

University 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

… and other colleagues from the EMR community

Prof. P. Barrade

Institute for Systems Engineering

University of Applied Sciences Western Switzerland

PhD in Electrical Engineering at University of Toulouse (1997)

Research topics: Power Electronics, Energy Storage, HIL Simulation, Hybrid Systems

31



- Some references -

A. Bouscayrol, & al. "Multimachine Multiconverter System: application for electromechanical drives", European

Physics Journal - Applied Physics, vol. 10, no. 2, May 2000, pp. 131-147 (common paper GREEN Nancy, L2EP Lille

and LEEI Toulouse, according to the SMM project of the GDR-SDSE).

A. Bouscayrol, "Formalism of modelling and control of multimachine multiconverter electromechanical systems” (Texte

in French), HDR report, University Lille1, Sciences & technologies, December 2003

A. Bouscayrol, J. P. Hautier, B. Lemaire-Semail, "Graphic Formalisms for the Control of Multi-Physical

Energetic Systems", Systemic Design Methodologies for Electrical Energy, tome 1, Analysis, Synthesis and

Management, Chapter 3, ISTE Willey editions, October 2012, ISBN: 9781848213883

K. Chen, A. Bouscayrol, W. Lhomme, "Energetic Macroscopic Representation and Inversion-based control: Application

to an Electric Vehicle with an electrical differential”, Journal of Asian Electric Vehicles, Vol. 6, no.1, June issue, 2008,

pp. 1097-1102.

P. Delarue, A. Bouscayrol, A. Tounzi, X. Guillaud, G. Lancigu, “Modelling, control and simulation of an overall wind

energy conversion system”, Renewable Energy, July 2003, vol. 28, no. 8, p. 1159-1324 (common paper L2EP Lille and

Jeumont SA).

J. P. Hautier, P. J. Barre, "The causal ordering graph - A tool for modelling and control law synthesis", Studies in

Informatics and Control Journal, vol. 13, no. 4, December 2004, pp. 265-283.

W. Lhomme, “Energy management of hybrid electric vehicles based on energetic macroscopic representation”, PhD

Dissertation, University of Lille (text in French), November 2007 (common work of L2EP Lille and LTE-INRETS

according to MEGEVH network).

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