«SYSTEM, ENERGY AND CAUSALITY»

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1 EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation «SYSTEM, ENERGY AND CAUSALITY» Prof. Alain BOUSCAYROL (L2EP, University Lille1, France) Prof. C.C. CHAN (University of Hong-Kong, China)

- Comple multi-physical s - More efficient s with same performances

Eample: VAL subway (Siemens) 2 1984 VAL 206 First automatic Subway

loss reduction more energy recovery How to ensure high dynamical and

2 - Comple multi-physical s - More efficient s with same performances New s for reduction of energy consumption for higher performances Eample: VAL subway (Siemens) VAL 206 First automatic Subway 2000 VAL 208 new PM machines 201 NeoVAL new supply position accuracy loss reduction more energy recovery How to ensure high dynamical and efficiency? (double objective : dynamics and energy) multi-objective control

- Comple multi-physical s - 3 More comple s Hybrid s several technologies and operations to combine Eample: THS from Toyota Mechanical power path Electrical power path

3 - Comple multi-physical s - 3 More comple s Hybrid s several technologies and operations to combine Eample: THS from Toyota Mechanical power path Electrical power path Generator Inverter Boost Battery Engine ECU Motor Power split How to manage the various power flows? How to optimise energy consumption? multi-layer control

4 - Typical study procedure - Simulation for ever! Launching Matlab/Simulink is more and more a Pavlov refle 4 real?#@!&? simulation But: Why simulation? Which constraints and objectives? Which level of accuracy? How to be sure of the results? behavior study

5 EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation «1. Model, Representation and Simulation» What different steps before simulation?

6 - From real s to simulation - model representation 6 simulation real Limitation to main phenomena in function of the objective Organization of the model to highlight some properties Intermediary steps are required for comple s

7 - Basic eample - model representation 7 simulation real v l L d dt i L Ri L V L 1 R+Ls I L Step 1 L.s+R scope smoothing inductor (low frequency dynamical model) (bloc diagram +Laplace) (Simulink +Range Kutta)

8 - Different categories - model representation 8 simulation real dynamical / quasi-static / static structural/functional causal/non-causal backward / forward Different possibilities at each step in function of the objective

9 - Limitation of classical bloc diagrams - 9 EUREKA! VDC k 3 1+t 3 s i filtrre i hach k 3 1+t 3 s Finger in the pockets! i He1 u filtrre c He1 c Hi c He2 [K] [K] i He [K] i He2 u He1 u He2 k 2 1+t 2 s k 2 u He i ee1 i ee2 k mcc iei k 1 1+t 1 s 1+t 2 s k mcc e ee1 e ee2 W B1 k bog C M1 k bog C M1 k bog k bog F bog1 F tot F bog2 F res M s v rame Remember, See the wood before the trees! But block diagrams: can be confusing for comple s are limited to continuous and linear s do not highlight energy properties do not highlight interaction between subs

10 EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation «2. System and Interaction» How to connect multi-physical subs?

11 - Systemic approach - System = interconnected subs organized for a common objective, in interaction with its environment 11 Systemic = science of study of s and their interactions Cartesian approach = the study of subs is sufficient to know the behavior (without considering their interactions) Interactions is the keyword

12 - Input and output of a - 12 Input: variable produced by the environment, imposed to the for evolution (independent of the ) Output: consequence of the evolution, imposed to its environment (not directly dependant on the environment) Input System Output Environment & System must be defined first! Environment

13 - Interaction principle - 13 Interaction principle Each action induces a reaction S1 action reaction S2 power Eample Power echanged by S1 and S2 = action réaction V bat battery V bat load V bat i load i load battery load P=V bat i load

14 - Interaction mistake - 14 If the interaction principle is not respected for 1 sub S1 action S2 Error in the energy analysis for the whole (reaction = 0) Power = 0 VDC k 3 1+t 3 s i filtrre i hach k 3 1+t 3 s i He1 u filtrre c He1 c Hi c He2 [K] [K] i He [K] i He2 u He1 u He2 k 2 1+t 2 s k 2 u He i ee1 i ee2 k mcc iei k 1 1+t 1 s 1+t 2 s k mcc e ee1 e ee2 W B1 k bog C M1 k bog C M1 k bog k bog F bog1 F tot F bog2 F res M s v rame

15 - Systemic and Cartesian approaches - System = interconnected subs 15 Systemic approach Study of subs and their interactions Holistic property: associations of sub induce new global properties. Cartesian approach The study of subs is sufficient to know the behaviour. Cybernetic ic black bo approach. behaviour model Cognitive ic physical laws knowledge model For better performances of a Interactions and physical laws must be considered!

16 - Systemic eample - DC machine and smoothing inductor i L f r f u i u 2 16 L m r m u 2 i e u u 2 L f di dt u u 2 r f i L m di dt u 2 e r m i L f +L m r f +r m u i e di ( L f Lm ) u e ( rf rm dt )i Association of both subs must be studied globally L r f f L r m m L r f f L r m m

17 EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation «3. Energy and Causality» How to manage energy in the best way?

18 - Energetic approach - Energy = amount of work that can be performed by a force, an object, a 18 Ideal energy conversion: energy conservation (no losses) and instantaneous transfer (no delay) but Energy dissipation: losses, reduction of efficiency Energy accumulation: delay in energy transfer Energy accumulation in subs is key transformation for safety and efficiency

19 - Causality principle - 19 Principle of causality physical causality is integral input output? cause effect t dt OK in real-time area knowledge of past evolution t 1 slope impossible in real-time knowledge of future evolution d dt

20 Eample d vc ic C vc C i dt R c v C 2 c v c E Causality principle - i c v C delay no energy disruption 20 v C d dt i c For energetic s physical causality is VITAL risk of damage

21 - causality mistake - 21 If the causality principle is not respected for 1 sub chopper Voltage Scaps Risk of damage! No real-time management VDC k 3 1+t 3 s i filtrre i hach k 3 1+t 3 s i He1 u filtrre c He1 c Hi c He2 [K] [K] i He [K] i He2 u He1 u He2 k 2 1+t 2 s k 2 u He i ee1 i ee2 k mcc iei k 1 1+t 1 s 1+t 2 s k mcc e ee1 e ee2 W B1 k bog C M1 k bog C M1 k bog k bog F bog1 F tot F bog2 F res M s v rame

22 - Comparison of modelling tools - Energy & System 22 Energetic Puzzles (Laplace, France) Bond Graph (USA, The Netherlands ) Power Oriented Graph (Italy) Signal Flow Diagram (Germany, Japan...) Structural description for analysis and design 1 0 mathematical model global controls Block diagrams COG (L2EP-LEEI, France) EMR (L2EP, France) functional descriptions for simulation and control Remember, Dr. B, divide and conquer! inversion graphs cascaded control

EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation = subs in interaction best performances require an ic approach energy = respect of the physical causality energy

23 EMR 17 Lille June 2017 Summer School EMR 17 Energetic Macroscopic Representation = subs in interaction best performances require an ic approach energy = respect of the physical causality energy management requires a causal approach control -> inversion of a causal model of the in order to respect its energy properties graphical description = model organization useful intermediary step Remember, follow a disciplined procedure!

24 - References - 24 P. J. Barre, & al, "Inversion-based control of electromechanical s using causal graphical descriptions", IEEE-IECON'06, Paris, November A. Bouscayrol, & al. "Multimachine Multiconverter System: application for electromechanical drives", European Physics Journal - Applied Physics, vol. 10, no. 2, May 2000, pp (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 s", EPE'05, Dresden (Germany), September (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 , April 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 (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 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 H. Paynter, "Analysis and design of engineering s", MIT Press, R. Zanasi, R. Morselli, "Modeling of Automotive Control Systems Using Power Oriented Graphs", IEEE-IECON'06, Paris, November 2006.

«About energy and causality principles»

EMR 16 UdeS - Longueuil June 2016 Summer School EMR 16 Energetic Macroscopic Representation «About energy and causality principles» Prof. X. KESTELYN 1, Prof. A. BOUSCAYROL 2, Prof. CC. CHAN 3 1 L2EP,