EMR’11 Joint Summer School EMR’11 Lausanne … · design Energetic Puzzles (Laplace, France)...

EMR’11 Lausanne July 2011

Joint Summer School EMR’11 “Energetic Macroscopic Representation”

Prof. Alain BOUSCAYROL L2EP, University Lille1, MEGEVH network,

[email protected]

Prof. Alfred RUFER, Dr. Philippe BARRADE LEI, Ecole Polytechnique Fédérale de Lausanne,

[email protected]

EMR’11, Lausanne, July 2011 3

Model = description based on physical laws (validity range function of assumptions)

Representation = organisation of a model in order to highlight some properties

vC ic

vC ic

Example

vC C ic

mathematical model

state space representation

transfer function

bloc diagram

COG

Cs 1

- Model and representation -


real system

system model

system representation

- Simulation of a system (1) -

system simulation

model objective

limited validity range

organization

valuable properties

behavior study

prediction


real system

system model

system representation

system simulation

Intermediary steps are required for complex systems

- Simulation of a system (2) -

Classical way (e.g. Matlab-Simulink©)


different kinds of objectives

different kinds of modelling

Objectives: • component design/optimization • component control • system analysis (efficiency…) • energy management of the system • ….

Modelling: • structural/functional models • static/dynamic models • causal/ acausal representations • backward/forward simulation • ...

Which model?

[Chan 2010]

- Model objectives -


A typical example from the domain of electrical engineering

- Functional representations -


The use of space phasors

Real and Immaginary parts



Rotating Reference frame

Stationary Reference frame

(Phasors Space Vectors)

Some properties depend from the definition of the reference frame!!



Rotating Reference frame

Real and Immaginary parts



A DC current machine fed with a bidirectionnal VSC

- Structural diagrams and interfaces -


Multidisciplinary studies:

Electrical engineers know in principle how to adapt models (p.u. systems)

Example of calculation of the torque in a synchrounous motor



Even the behaviour of the mechanical system is not difficult to integrate



u

i

Physical quantities

i

u

i

« Informations , signals»

Functional representation

(Voltage source)

- From the physical quantity to the signal -


u

i

Physical quantities

i

u

i « Informations , signals»

Functional representation

(Current source)

- From the physical quantity to the signal -

EMR’11, Lausanne, July 2011 16 - The complexity of the interface (physical quantity) -

two DC machines system

PSIM (structural) Matlab-Simulink (functionnal)

machines connected by a unique link (shaft)

machines connected by two links (torque/speed)


area

knowledge of past evolution

OK in real-time

Principle of causality physical causality is integral

input output

cause effect

t1 t

x

knowledge of future evolution

slope

?

impossible in real-time

- Causality principle -

EMR’11, Lausanne, July 2011 18 - Causality principle -

Example

vC C ic

delay no energy disruption

vC ic

risk of damage

vC ic d dt

For energetic systems physical causality is VITAL

EMR’11, Lausanne, July 2011 19 - The questions about causality -

• Remember: • A state-space quantity (for example X(t) ) represents a given content of stored energy

– Examples • Inductors, capacitors (el. engineering) • Speed or rotational speed of masses (mech.

engineering) • Also position, height with gravity (potential energy) • Ion concentration (chem. engineering)

The problem: dx/dt, the derivation Question : how to chose the dynamic model, in order to avoid the «infinite» values of instantanous power


- Very simple examples -

No energy storage

Energy storage inside of the inductor

Energy storage inside of the capacitor

EMR’11, Lausanne, July 2011 21 - No energy storage -

EMR’11, Lausanne, July 2011 22 - Energy storage inside of the inductor -

Io: Causal function « A current is injected through the resistor »


- Energy storage inside of the inductor -

(!) derivation of the state variable


- Energy storage inside of the capacitor -

Uc: causal function « A Voltage is applied to the terminals of the resistor »


- Energy storage inside of the capacitor -

(!) derivation of the state variable (!) derivation of the input quantity


Energy & System

mathematical model

global controls

analysis design

Energetic Puzzles (Laplace, France)

Bond Graph (USA, The Netherlands…)

Power Oriented Graph (Italy)

Signal Flow Diagram (Germany, Japan...)...

1 0

- Comparison of modelling tools -

COG (L2EP-LEEI, France)

EMR (L2EP, France)

causal descriptions

for simulation and control

cascaded control

inversion graphs

EMR’11, Lausanne, July 2011 28 - Graphical modelling tools -

1960 2000 2020 1980

use of Petri Nets

Power Electronics

discrete event systems

Bond Graph

system analysis and design (structural approach)

Mechanical Engineering

Electrical Engineering

USA The Netherlands worldwide

Causal Ordering Graph (COG)

drive control (functional approach)

Electric Drives France

Energetic Macroscopic Representation (EMR)

system control (functional approach)

Electric Systems France Canada

Switzerland Denmark China…

Energetic Systems


e: effort

f: flow

- Bond Graph -

EMR’11, Lausanne, July 2011 30 - Bond Graph -


The principle of causality

- Bond Graph -


Schematic representation of a DC motor fed by a power electronic converter

- Bond Graph: example -


Bond Graphs - Bond Graph (example) -


Zanasi R. , Power-oriented graphs for modeling electrical machines « Electrotechnical Conference MELECON’96, May 1996, vol. 3, p. 1211-1214

- Power Oriented Graph (POG) -

EMR’11, Lausanne, July 2011 37 - Power Oriented Graph (POG) -


Schönfeld R. , Leitner H.G. Power flow and information flow in motion control systems EPE-PEMC Riga, Sept. 2004

- Power Flow Diagram (PFD) -

EMR’11, Lausanne, July 2011 39 - Power Flow Diagram (PFD) -


Remember, See the wood before the trees!

Use of GRAPHICAL DESCRIPTIONS for modelling and control of non-elementary systems

System: sub-systems in interactions organised for a common objective

transportation systems renewable energy applications production machines drives in industry process tactile interfaces...

intermediary step for another view of the system

• synthetic description • respect of physical properties • linked to classical modelling

new ways to design, analyse simulate and manage such systems

- Graphical description -


iei

VDC iHi uHi

voiture

vrame

ufiltre

iHe2 iee2

iHe1 iee1 uHe1

uHe2

ihach

ifiltre

+ CM1

ΩB1 CM2

ΩB2

Fres

- Example of a railway traction system -

iHe1

M s

vrame

Fres

Ftot

kbog

kbog

kbog

kbog

Fbog1

Fbog2

k1 1+τ1s

x CM1

ΩB1

uHe x

CM1

x

k2 1+τ2s

kmcc

iei iee1

x

k2 1+τ2s kmcc

iee2

uHe1

x

x

cHe1

x

x

x

x

uHe2 eee2

eee1

iHe

iHe2

k3 1+τ3s

ihach

k3 1+τ3s

ifiltrre ufiltrre VDC

[K]

cHi [K]

cHe2 [K]

Simplified block diagram causality? action/reaction?


iei

VDC iHi uHi

voiture

vrame

ufiltre

iHe2 iee2

iHe1 iee1 uHe1

uHe2

ihach

ifiltre

+ CM1

ΩB1 CM2

ΩB2

Fres


Causal Ordering Graph (COG)

ufiltrre

vrame

Fres

CM1

ΩB1

eei

iee1 cHe1

iHe2 ifiltrre ufiltrre VDC

cHi uHi iei

uHi

iee1 Fbog1

vrame

CM2

ΩB2

Fbog2

ufiltrre uHe2 cHe2

iee2

iee1

iHe2

iHi

iHe1

[Hautier 96] [Guillaud 01]

causality OK action/reaction?


iei

VDC iHi uHi

voiture

vrame

ufiltre

iHe2 iee2

iHe1 iee1 uHe1

uHe2

ihach

ifiltre

+ CM1

ΩB1 CM2

ΩB2

Fres


Bond Graph (BG)

[Paynter 61] [Dauphin 99]

R : Rind2

1

vrame

Fres

CM1

ΩB1 eei1 cHe1

ifiltre ufiltre

Se : VDC cHi

uHi iei

uHe1 iee1

Fbog1 vrame

iHi

iHe1 1

VDC 0

R : Rf

ifiltre ufiltre

I : Lf C : Cf

MTF 1

MTF ufiltre R : Rind1

I : Lind1

1

I : Lind2

MGY

iei

eei2 iei

TF

1I : M vrame Charge

CM2

ΩB2 MGY TF

Fbog2 vrame

1

R : Rex1

I : Lex1

1cHe1 uHe2 iee2 MTF 1

R : Rex1

I : Lex1

iHe2 ufiltre

physical causality? action/reaction OK


iei

VDC iHi uHi

voiture

vrame

ufiltre

iHe2 iee2

iHe1 iee1 uHe1

uHe2

ihach

ifiltre

+ CM1

ΩB1 CM2

ΩB2

Fres


Energetic Macroscopic Representation (EMR)

[Bouscayrol 00] [Bouscayrol 05]

rail

filtre

mise en // enroulements

hacheurs

conv. EM

bogie

couplage

rame

environnement

Ftot vrame

iHe1

M2

eee2 iee2

VDC ihach

uHe2 iee2 He2

CM2 ΩB2 B2

FB2

vrame

vrame

Fres

cHe2

SM SE

ufiltre iHi

uHi iei Hi

cHi

iei eei

M1 CM1 ΩB1 B2

FB1 vrame

iei eei1 iei eei2

ufiltre

ifiltre

ufiltre iHe2

eee1 iee1 uHe1

iee1 He1

cHe1

ufiltre

mise en série

physical causality OK action/reaction OK


- -

Multi-physical system

Real-time control

Systemic approach

Dynamical modeling Causal modeling

Energy management Energetic approach Causal modeling

System control Functional description

Moreover a graphical description could be a valuable intermediary step for such complex systems

- Which model for EV/HEV control? -

EMR’11, Lausanne, July 2011 47 - Different control levels -

Energy management of HEVs: Energy management of local subsystems Energy management of the whole system (co-ordination of subsystems)

Two control levels can be organized: - local control - system supervision

Dynamic and causal models Quasi-static

models

compatibility in term of

inputs/outputs

compatibility of the

control levels [Delarue & al 2005]

EMR’11, Lausanne, July 2011 48 - Different control levels (example) -

BAT

ICE

VSI EM

Fuel Parallel HEV Trans.

fast subsystem controls

EM control

ICE control

Trans control

Energy management (supervision/strategy)

driver request

slow system supervision

EMR’11, Lausanne, July 2011 49 - Local control -

EM control

ICE control

Trans control

Local energy management: must take into account power flows in all parts of subsystems

Classical controls of subsystems: required dynamic and energetic models to manage power flows in real-time


- Energy management methods -

[Salmasi 2007]

Energy management (supervision/strategy)

driver request

Rule-based

deterministic rule-based

fuzzy rule-based

state machine / power follower/ thermostat control…

predictive / adpative / conventional…

Optimization based

global optimization

real-time optimization

Dynamic programming / stochastic DP / Game theory / Optimal control….

Robust control / Model predictive / decoupling control / l control…



system = subsystems in interaction best performances require a systemic approach

energy = respect of the physical causality energy management requires a causal approach

control -> inversion of a causal model of the system in order to respect its energy properties

graphical description = model organization useful intermediary step

Remember, follow a disciplined procedure!


- References -

P. J. Barre, & al, "Inversion-based control of electromechanical systems using causal graphical descriptions", IEEE-IECON'06, Paris, November 2006.

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, G. Dauphin-Tanguy, R Schoenfeld, A. Pennamen, X. Guillaud, G.-H. Geitner, "Different energetic descriptions for electromechanical systems", EPE'05, Dresden (Germany), September 2005. (common paper of L2EP, LAGIS and University Dresden).

C.C. Chan, “The state of the art of electric, hybrid, and fuel cell vehicles", Proceedings of the IEEE, Vol. 95, No.4, pp. 704-718, April 2007.

C.C. Chan, A. Bouscayrol, K. Chen, "Philosophy of Engineering and Modelling of Electric Drives”, International Conference on Electrical, Keynote, October 2008, Wuhan (China)

C. C. Chan, A. Bouscayrol, K. Chen, “Electric, Hybrid and Fuel Cell Vehicles: Architectures and Modeling", IEEE transactions on Vehicular Technology, vol. 59, no. 2, February 2010, pp. 589-598 (common paper of L2EP Lille and Honk-Kong University).

G. H. Geitner, "Power Flow Diagrams Using a Bond graph Library under Simulink", IEEE-IECON'06, Paris, November 2006.

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.

H. Paynter, "Analysis and design of engineering systems", MIT Press, 1961.

F. R. Salmasi, "Control strategies for Hybrid Electric Vehicles: evolution, classification, comparison and future trends", IEEE Trans. on Vehicular Technology, September 2007, Vol. 56, No. 3, pp. 2393-2404

R. Zanasi, R. Morselli, "Modeling of Automotive Control Systems Using Power Oriented Graphs", IEEE-IECON'06, Paris, November 2006.


Interaction principle Each action induces a reaction

action

reaction

S2 S2

Power exchanged by S1and S2 = action x réaction

power

- Interaction principle -

Example

battery load

Vbat Vbat

iload

load battery Vbat

iload

P=Vbat iload

EMR’11 Joint Summer School EMR’11 Lausanne … · design Energetic Puzzles (Laplace, France)...

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