Tony LETROUVE L2EP, University Lille1, PSA Peugeot Citroën, MEGEVH network

Transcription

1 EMR 12 Madrid June 2012 Joint Summer School EMR 12 Energetic Macroscopic Representation EMR AND INVERSION-BASED CONTROL FOR HIL SIMULATION OF A D A DOUBLE PARALLEL HEV Tony LETROUVE L2EP, University Lille1, PSA Peugeot Citroën, MEGEVH network Tony.letrouve@mpsa.com Walter LHOMME, Alain BOUSCAYROL L2EP, University Lille1, MEGEVH network Nicolas DOLLINGER, Fabien MERCIER CALVAIRAC PSA Peugeot Citroën

2 - Outline Context et objectives 2. HIL Simulations 3. Conclusion & perspectives

3 EMR 12 Madrid June 2012 Joint Summer School EMR 12 Energetic Macroscopic Representation CONTEXT AND OBJECTIVES PhD thesis objectives Relevant definitions Industrial and scientific contexts

4 - Context and Objectives - 4 Thesis title : Methodology of energy managment and Real time application for HEV Using EMR T. Letrouvé GEE/ Control team Laboratory of Electrical Engineering and Power Electronics Supervisors L2EP : A. Bouscayrol, W. Lhomme DRD/DRIA/TASE/CO2E Control and Optimisation of Energy and Emission Supervisors PSA : N. Dollinger, F. Mercier Calvairac Scientific issues: Innovative approach of a systematic control from simulation to prototype, Coupling between functional and structural approaches, Systematic strategy.

5 Σ Modelling 1 Assumption 1 - Definitions - Description 11 Description 12 5 Sim. Soft. 121 Sim. Soft. 122 Sim. Soft. 123 Assumption 2 Description 21 Modelling 2 Description 22 Sim. Soft. 211 Sim. Soft. 212 Sim. Soft. 213 Modelling Mathematical description of the system behaviour defined according to assumptions associated to objectives (static / dynamic model, causal or not ) Description Model organization which permits to highlight some system properties. No assumption between model and description. (State description, BondGraph, EMR, ) Simulation software Computer organization of a description which permit to simulate the system behaviour. (C language, Range Kutta method, )

6 Professional approach for the control elaboration of a hybrid electric vehicle Modelling - Problematic and Objectives - L2EP/MEGEVH approach Modelling for the control elaboration of a hybrid electric vehicle 6 Control 1 Description Control Simulation Simulation Control 2 Emulation Prototype Prototype Industrial objective : Use a description tool like EMR to structure the control from simulation to prototype. Rear Electric machine Battery HV LV Load Front Electric machine ICE LV Battery GB Cltch

7 EMR 12 Madrid June 2012 Joint Summer School EMR 12 Energetic Macroscopic Representation HIL S SIMULATION EMR and IBC of the studied vehicle Emulations done Emulation results

8 Sources - EMR of the studied System - Rear EM Dog box GB Rear Trans. Non linear conversion elements 8 ICE Front EM T REM T FEM P B P dogbox clutch GB Front Trans. v véh F res Env. F brakes Strategy Bat HV Bat LV T ice Stator Pcltch k boîte Coupling elements DC/ DC T dem m DC/DC Drivers actions Conversion elements Rear Electric machine Front Electric machine HVBattery Load BT ICE LV Battery GB Cltch

9 - Inversion based control of the studied system - 9 REM m ond1 p crabot FEM m ond2 v véh Env. SM ICE F res SE C mth-ref SM C mth p emb k boîte Brakes SM SE V bat-bt MCC dem F frein-ref k dem kdem m hachdc/dc SE V bat-bt-ref i bat-bt-ref Objective: Control the current in the low voltage battery Tuning variable: m DC/DC

10 - Inversion based control of the studied system - 10 REM m ond1 p crabot FEM m ond2 v véh Env. SM ICE F res SE C mth-ref SM C mth p emb k boîte Brakes SM SE V bat-bt MCC dem F frein-ref k dem kdem m hachdc/dc SE Bloqué V bat-bt-ref Ω arbre-ref K rep-av Mth/mel-av K rep-av G/D v ref i bat-bt-ref Patinage Bloqué K rep frein v véh-ref K rep av/ar Ω arbre-ref Objective: Control the vehicle speed Tuning variables: T mth_ref,m ond2,m ond1,f brakes_ref Ouvert K rep-ar G/D STRATEGY

11 - What is a PHIL Simulation? - What is a power Hardware-In-the-Loop simulation? 11 Sources models Control signals Sub-system 1 models I S measures Sub-system 2 models Load Models Simulation environment Control algorithm References A. Bouscayrol, Hardware-In-the-Loop simulation, Industrial Electronics Handbook, second edition, tome 3, Chapter M35, Editions Taylor & Francis, Chicago

12 Example of a EV Power HILs - Example of a PHIL Simulation - 12 Battery Electric machine Electric machine Network Objectives of a reduced scale HILs validate the real time portability of the control done in simulation, validate indirectly models used in simulation, test the fault tolerance of the system, precise the requirements. Objectives of a full scale HILs validate directly models used in simulation, take into account all the limitation and component constraints. Energy source Control Signals Tested subsystem Electric machine 1 ECU Source measures Control algorithm Interface system Electric machine 2 Emulated subsystem Emulation source Control of the EM Emulated load References

13 - HIL simulation - 13 Rear EM Front EM Supercaps Load 2,2 kw

14 Plateforme HIL Scap Rear Emul. EMR and IBC for HIL EM simulation of a double parallel Fr HEV T REM-ref Front EM T FEM-ref Emul. R+Ice Net. 14 T ice-ref Bat HV Load 2,2 kw ICE P B Dog box P dogbox clutch P cltch GB GB k boîte Rear Trans. Front Trans. F tot v veh Env. Control and emulated part Strategy

15 Plateforme HIL Scap Rear Emul. EMR and IBC for HIL EM simulation of a double parallel HEV Fr T REM-ref Front EM T FEM-ref ICE T ice-ref Emul. R+Ice Net. 15 Control and emulated part Strategy

16 - Validation of the battery emulation N DCM-mea (rpm) Vitesse de rotation de l'arbre des machines [trs/min] Tesion de la batterie de reference et réponse du système U bus (V) bat émulée U bus - measure U bat réference bus - emulated Peugeot Ion 10 Courant de la machine de traction (DC) 0 I sc-mea (A) Battery emulation Electric machine Chassis emulation 0. 8 E m u la te d S O C o f t h e b a t te r y SOC -emul (%)

17 17 Emulated HV battery Power electronics and control Front Electric machine Rear Powertrain Front P.train + ICE Rear Electric machine

18 - Real time interface developed - 18

19 v hev-ref EMR and IBC for HIL simulation of a double parallel HEV - Simulation results - P cltch Open 19 close N rem-mes Clutch N fem-mes T rem-ref FEM I C E Battery HV REM T fem-ref DogBox SoC _min_stop SoC Operating mode SoC _min_drive

20 EMR 12 Madrid June 2012 Joint Summer School EMR 12 Energetic Macroscopic Representation Conclusion & Perspectives

21 - Conclusion - Development of EMR and Inversion Based control of the HYbrid 4 architecture 21 Modélisation Représentation Commande Validation, using a reduced scale HIL simulation, de la of the real time portability of the control and strategy done in simulation. Simulation Emulation Prototype Perspectives Modification et optimization of the strategy Use a full scale HIL simulation: Take into account component limitation and constraints Direct validation of models used in simulation Use this deduced control in the real prototype

22 PERSPECTIVES Prototype 22 PTMU 1 IBC Caractéristics: ICE : DV6TED4 Rear EM : PARVEX 20kW Battery : Li ion 10MJ

23 EMR 12 Madrid June 2012 Joint Summer School EMR 12 Energetic Macroscopic Representation BIOGRAPHIES AND REFERENCES

24 - Authors - 24 Tony LETROUVE University Lille 1, L2EP, PSA Peugeot Citroën MEGEVH PhD student at University Lille 1 science and technology (since 2009) Research topics: EMR, HIL simulation, Prototyping on HEV. 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 Dr. Walter LHOMME University Lille 1, L2EP, MEGEVH, France Associate professor in University Lille 1 science and technology PhD in Electrical Engineering at University of Lille 1 (2007) Dr. Nicolas DOLLINGER, Fabien MERCIER CALVAIRAC PSA Peugeot Citroën France, France

25 - References - [Letrouvé 09a] T. Letrouvé; P. Delarue; A. Bouscayrol, Modelling and control of a double parallel hybrid electric vehicle using Energetic Macroscopic Representation, Electromotion 09, Lille, France, July [Letrouvé 09b] T. Letrouvé; A. Bouscayrol; W. Lhomme, Influence of the clutch model in a simulation of a parallel Hybrid Electric Vehicle, IEEE VPPC 09, Dearborn, USA, September [Letrouvé 10] T. Letrouvé; A. Bouscayrol; W. Lhomme, N. Dollinger, F. Mercier Calvairac, Different models of a traction drive for an electric vehicle simulation, IEEE VPPC 10, Lille, France, September [Bouscayrol 11] A. Bouscayrol, P. Barrade, L. Boulon, K. Chen, Y. Cheng, P. Delarue, B. Lemaire-S , T. Letrouve, W. Lhomme, P. Sicard, Teaching drive control using Energetic Macroscopic Representation Summer schools, EPE 2011, Birmingham, United Kingdom, August 2011 [Letrouvé 11] T. Letrouvé; A. Bouscayrol; W. Lhomme, N. Dollinger, F. Mercier Calvairac, Inversion Based Control of a double parallel Hybrid Electric Vehicle: Validation in a structural software, IEEE VPPC 11, Chicago, USA, September [Letrouvé 12] T. Letrouvé; A. Bouscayrol; W. Lhomme, N. Dollinger, F. Mercier Calvairac, Reduced-scale Hardware-In-the-Loop Simulation of a Peugeot 3 8 HYbrid4 vehicle, IEEE VPPC 12, Seoul, Korea, October HY HY4