«Different concepts for Hardware-In-the-Loop simulation»

Transcription

1 HIL 16 summer school Lille, 1-2 September «Different concepts for Hardware-In-the-Loop simulation» Prof. Alain BOUSCAYROL L2EP, University Lille1, MEGEVH network, IEEE-VTS DL

2 Outline 2 1. WHAT IS HIL SIMULATION? 2. WHICH MODELS FOR HIL SIMULATION? 3. Different types of HIL SIMULATION?

3 Graphical rules 3 Physical power system (orange) process (blue) mathematical model (purple) power variables signal variables SIMULATION SOFTWARE REAL-TIME CONTROLLER SUBSYSTEM UNDER TEST

4 4 Scientific context L2EP Lille MEGEVH Network IEEE VTS DL program

5 L2EP Lille 5 Laboratory of Electrical Engineering and Power electronics (L2EP) members : 30 professors and associate professors, 40 PhD students, 12 lab s staff, Post-doctoral positions, Master students, etc.

6 MEGEVH Network 12 (Energy management of Hybrid and Electric Vehicles) Coordination: Prof. A. Bouscayrol 6 projects 4 PhDs in progress 11 PhDs defended 8 industrial partners 10 academic Labs

7 MEGEVH philosophy theoretical developments MEGEVH-macro MEGEVH-strategy MEGEVH-optim MEGEVH-FC MEGEVH-store Development of modeling and energy management methods independently of the kind of vehicle 13 experimental plate-forms Paper Prize Award of IEEE-VPPC 08 Paper Prize Award of IEEE-VPPC 12 Reference vehicles Paper Award EPE 14 ECCE Europe Best paper Award IET-EST journal 2015

8 VTS Distinguished Lecturer Program IEEE - Institute of Electrical & Electronics Engineers Non-profit professional organization for advancing technological innovation and excellence 400,000 members from 160 countries (30 % students) 38 societies on technical interest Activities scientific workshop, conferences, publications, standards database IEEE Xplore, 3.5 millions documents, etc 14 IEEE Vehicular Technology Society (VTS) Technical topics land, airborne and maritime services mobile communication, vehicle electro-technology 2 publications and 4 annual conferences Distinguished Lecturer Program Prof. A. Bouscayrol HIL simulation EMR formalism EVs and HEVs

9 15 1. What is of HIL simulation? Software simulation HIL simulation Models for HIL simulation

10 Industrial V-cycle 16 Technical requirements Prototype time System specifications Integration tests Component design Component tests Accuracy level component realization

11 Software intermediary axis 17 Technical requirements Virtual Prototype Prototype time System specifications Virtual test Integration tests Component design Component tests Accuracy level component realization

12 HIL simulation test 18 Technical requirements Virtual Prototype Prototype time System specifications Virtual test Integration tests Component design Component tests Accuracy level component realization

13 HIL simulation approach Example of an EV prototype 19 production simulation HIL platform Component design component realization Component tests the more test are made at HIL the less prototypes are developed

14 System & 20 Example of an electric drive for traction signals power electronics POWER SYSTEM electric machine mechanical power train process CONTROLLER BOARD (ECU) measurements How to develop the system? Software simulation

15 Example of an EV traction 21 V bat i chop s 11 s 21 u chop i dcm T im W gear T gear W wh1 T diff1 W diff W wh2 T diff2 Traction of an EV: Battery + chopper + DC machine + differential + 2 driven wheels drive switching order s ij battery + chopper u chop DC machine T dcm mechanical power train i dcm W gear drive V bat_meas idcm_meas W gear_meas v ev_meas?

16 Software simulation 22 simulation of the system and the in a simulation software: development / safety / gain of time... signals power electronics SIMULATION ENVIRONMENT electric machine mechanical power train process measurements models

17 Example of an EV traction system 23 u i chop chop m m V chop bat t chopidcm (1) Assumptions: 1 single equivalent wheel u chop T dcm switching order s ij battery + chopper (1) i dcm DC machine (2) (3) W gear mechanical trans. (4)-(6) drive V bat_meas iim_meas W gear_meas v ev_meas? u chop L d dt i dcm Ri dcm e T e dc dcm dcm k (2) i dcm kw gear (3) F W tract gear m R m R gear wh gear wh T v dcm ev (4) F F res tract F F 0 res Av 2 ev M d dt v ev (5) Mgsin (6)

18 Limitation of software simulation 24 model accuracy simulation solver signals power electronics SIMULATION ENVIRONMENT electric machine mechanical power train process measurements ECU effects (discrete-time...) sensor effects (quantification, EMI..) How to check subsystems before real-time implementation? HIL simulation?

19 HIL simulation (1) 25 Hardware-In-the-Loop (HIL) simulation: one simulation part is replaced by an actual part signals process power electronics SIMULATION ENVIRONMENT electric electric mechanical mechanical machine machine power train power train CONTROLLER BOARD (ECU) Interface System Real-time simulation SUBSYSTEM UNDER TEST Example: test of ECU and Power Electronics

20 HIL simulation (2) 26 HIL simulation: Includes a hardware part, a software part and a specific interface HARDWARE process CONTROLLER BOARD (ECU) power electronics Interface System electric machine SOFTWARE mechanical power train HIL simulation = Real-time simulation (but including a hardware part) = Emulation

21 HIL simulation requirements HIL simulation = Hardware (energy conversion) + Models computed in real-time in dynamic interactions 27 energetic model causal model dynamical model HARDWARE power REAL-TIME SIMULATION efficient results require: an accurate model! an ideal interface system

22 28 2. Which models for HIL simulation? Models and organization Systemics and interaction

23 Typical study procedure 29 Simulation for ever! Launching Matlab/Simulink is more and more a Pavlov reflex real system But: Why simulation? Which constraints and objectives? Which level of accuracy? How to be sure of the results??#@!&? system simulation behavior study

24 From real system to simulation system model system representation 30 system simulation real system Limitation to main phenomena in function of the objective Organization of the model to highlight some properties Intermediary steps are required for complex systems

25 Basic example 31 system model system representation system simulation real system 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 +Runge Kutta)

26 Different categories 32 system model system representation system simulation real system dynamic / quasi-static / static structural/functional causal/non-causal backward / forward Different possibilities at each step in function of the objective

27 Static vs. dynamical models 34 Which model subsystem? Static model steady state operations no transient states fast computation time global behavior Dynamical model transient state operations but also steady state operations long computation time detailed behavior Quasi-static model static model + main time constant intermediary computation time intermediary behavior

28 Torque in Nm Example of electrical machine 35 static efficiency map 150 dynamic model i DC Speed in rpm T em U t DC 85 W P ( T, W) 88 em quasi-static model 85 + J d dt W T em T load fw T V Sd R S i Sd d Sd dt S Sq V Sq R S i Sq d Sq dt S Sd 0 R R i Rd d Rd R Rq dt 0 R R i Rq d Rq R Rd dt Lm p ( ) Rd isq Rq isd LR d J W Tem Tload fw dt em

29 Structural vs. functional description 36 How to describe a system? Structural description Physical structure in priority Physical links between subsystems Design application Functional description function priority Virtual links between subsystems Analysis and application Example v 2 i 1 m v 1 m i 2 3D Finite Element Model Mathematic model Assumption: Ideal transformer

30 Dedicated software 37 two DC machine system PSIM (structural) Matlab-Simulink (functionnal) machines connected by a unique link (shaft) machines connected by two links (torque/speed)

31 Structural vs. functional description (example) 38 structural I PAC q ph 2O 1 2F dv c O2 2e 2H H2O RtC Vc Rt I PAC 2 dt G 0 T PAC ) H 0 T PAC T PAC. S 0 T PAC E 0 P x Pscx Rdx q 2F 2F 1 x Q TPAC TH 2O PscH 2 PscO 2 E Acd ln Bcd ln I RT T PAC H 2O Rth P Sq0 S0 q 0 P q 0 c _ O2 ph 2O 4F Psc _ O2 VM EN V RmI PAC 2 3 Sq0 ' ' TPAC ' TPAC ' TPAC ' TPAC lntpac q ph 2O H2 2H 2e I PAC In I PAC V AT PACln BTPACln 1 E I PAC Sqn I0 Il I RT q PAC c _ H 2 H T 2 2H 2e 2F P PAC sc _ H E0 TPAC TPAC TPAC TPAC lntpac V N V M V c dpscx qx qcx q 1 xout Pscx P dt C q sx dx xout Rdx2 1 R H2 O2 H2O th 50exp 0,34q H 2O 2 functional

32 Causal vs. acuasal description 39 How to connect subsystem? Causal description fixed input and output output = integral function of inputs difficult interconnection subsystems basic solver T 1 W W T 1 T 2 J W d W T 1 T 2 dt Non-causal (acausal) description non-fixed inputs and outputs different relationships easy subsystem interconnection specific solver required simulation library T 1 T 2 T 2 W

33 Subsystem interconnexion Example ICE W W T 1 T 2 J d dt causal description 1 W T1 T2 W W T 2 T 3 J d dt 2 W T2 T3 electrical machine acausal description 40 T 1 T 2 J 1 W J 2 W T 1 T 3 J 1 J T 2 1 W T 2 T 3 T 2 d ( J1 J 2) W T1 T dt 3 derivative relationship T 1 T 3 J equ W specific solver

34 Causality principle 41 Principle of causality physical causality is integral input output x? cause effect t xdt OK in real-time area knowledge of past evolution t 1 slope impossible in real-time knowledge of future evolution dx dt

35 Causality principle 42 Example C i c v C i C d c v c 1 dt 2 c v c E 2 i c v C delay no energy disruption v C d dt i c For energetic systems physical causality is VITAL risk of damage

36 Causality mistake 43 If the causality principle is not respected for 1 subsystem chopper Voltage Scaps Risk of damage! No real-time management V DC 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 x x x x x x u He1 u He2 k 2 1+t 2 s u He i ee1 k mcc k 1 1+t 1 s k 2 i ee2 1+t 2 s k mcc i ei e ee1 e ee2 x x x x W B1 C M1 C M1 k bog k bog k bog k bog F bog1 F tot F bog2 F res M s v rame

37 Causality mistake He, guy! A new energy converter! I will press on the neck to model it When you discover a new process (!) You should apply the right Input If not 44 It was not a good idea! Don t forget to respect causality!

38 Systemic vs. Cartesian approach 47 System = interconnected subsystems Systemic approach Study of subsystems and their interactions Holistic property: associations of subsystem induce new global properties. Cartesian approach The study of subsystems is sufficient to know the system behaviour. Cybernetic systemic black box approach. behaviour model Cognitive systemic physical laws knowledge model For better performances of a system Interactions and physical laws must be considered!

39 Expected results 48 System 1 vs. System 2 Group made of individualists Team made of partners Cartesian approach Systemic approach Brazil 1 7 Germany

40 Interaction principle 49 Interaction principle Each action induces a reaction S2 action reaction S2 power Example Power exchanged by S1and S2 = action x réaction V bat battery V bat load V bat i load i load battery load P=V bat i load

41 Interaction principle 50 If the interaction principle is not respected for 1 subsystem S1 action S2 Error in the energy analysis for the whole system (reaction = 0) Power = 0 V DC 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 x x x x x x u He1 u He2 k 2 1+t 2 s u He i ee1 k mcc k 1 1+t 1 s k 2 i ee2 1+t 2 s k mcc i ei e ee1 e ee2 x x x x W B1 C M1 C M1 k bog k bog k bog k bog F bog1 F tot F bog2 F res M s v rame

42 54 3. Different types of HIL simulation Signal HIL simulation Power HIL simulation

43 Signal HIL simulation 55 The actual ler board containing the process is tested. signals power electronics electric machine mechanical power train process CONTROLLER BOARD (ECU) subsystem to test measurements Objectives: - assessment - reliability of ECU - fault operation of ECU -

44 Signal HIL simulation 56 signals power electronics SIMULATION ENVIRONMENT electric machine mechanical power train process CONTROLLER BOARD (ECU) SYSTEM UNDER TEST Interface System: measurements only signals equivalent measurements equivalent signals

45 Signal HIL simulation 57 Fast dynamic: FPGA? signals power electronics EMULATION CONTROLLER electric machine mechanical power train process CONTROLLER BOARD (ECU) SYSTEM UNDER TEST measurements Second ler board with its own interface

46 Example of signal HIL simulation 58 subsystem to test ECU u chop T dcm s ij battery + chopper (1) i dcm DC machine (2) (3) W gear mechanical trans. (4)-(6) drive V bat_meas idcm_meas CONTROLLER BOARD (ECU) EMULATION CONTROLLER W gear_meas SYSTEM UNDER TEST Remark: dynamic causal models u chop L d dt i dcm u chop Ri dcm e dcm (2) i dcm u chop dt

47 Power HIL simulation 59 The actual ler board and a power subsystem are tested. signals power electronics electric machine mechanical power train process CONTROLLER BOARD (ECU) measurements subsystem to test Objectives: - assessment - power device assessment - interactions (EMI ) -

48 Power HIL simulation 60 signals power electronics SIMULATION ENVIRONMENT electric machine mechanical power train process CONTROLLER BOARD (ECU) SYSTEM UNDER TEST Interface System: and power signals equivalent measurements power action and reaction

49 Power HIL simulation 61 signals power electronics emulation system SIMULATION ENVIRONMENT electric machine mechanical power train process emulation CONTROLLER BOARD (ECU) SYSTEM UNDER TEST Emulation system: interaction with hardware Emulation : of the emulation system and interaction with the model

50 Power HIL simulation 62 signals power electronics emulation system electric machine mechanical power train process CONTROLLER BOARD (ECU) SYSTEM UNDER TEST emulation EMULATION CONTROLLER The same ler board can be used for: of the emulation system real-time simulation of subsystems

51 Example of power HIL simulation (1) 64 subsystem to test u chop battery + chopper i dcm DC machine (2) (3) ECU must impose the same current example of emulation system L battery + chopper u chop i dcm emulation system i dcm_ref u chop i dcm current loop

52 Example of power HIL simulation (1) 65 real battery and chopper emulation system u chop i dcm L fast current loop small sampling period current loop drive i dcm_ref u chop_est DC machine (2) (3) mechanical trans. (4)-(6) ECU EMULATION CONTROLLER

53 Mechanical power HIL simulation 67 subsystem to test DC machine T dcm? mechanical trans. (4)-(6) ECU example of emulation system W gear must impose the same speed T dcm W gear W gear _ref speed / current loops

54 Example of mechanical power HIL simulation 68 real bat. & chopper real machine emulation system T dcm W gear speed / current loops drive W gear _ref T dcm_est mechanical trans. (4)-(6) ECU EMULATION CONTROLLER

55 69 3b. Full-scaled and reduced-scale HIL simulation Full-scale HIL simulation Reduced-scale HIL simulation

56 Full-scale power HIL simulation 70 Full-power subsystems are tested signals power electronics electric machine emulation system mechanical power train process emulation CONTROLLER BOARD (ECU) SYSTEM UNDER TEST EMULATION CONTROLLER Full-power emulation system is required The system under test can directly be implemented on the real process

57 Example of full-scale power HIL simulation 71 real bat. & chopper real machine emulation system (T es ) max > (T real ) max T dcm (W es ) max > (W real ) max (P es ) max > (P real ) max W gear T speed / current loops T dcm_est W drive W gear _ref mechanical trans. (4)-(6) (dynamics) es faster than (dynamics) mech trans ECU EMULATION CONTROLLER J es < J mech-trans

58 Reduced-scale power HIL simulation 72 Reduced-power subsystems are tested signals power electronics electric machine emulation system mechanical power train process emulation P A CONTROLLER BOARD (ECU) SYSTEM UNDER TEST EMULATION CONTROLLER Intermediary step before full-scale HILs Power adaptation (PA) is required if full-scale models are used

59 Reduced-scale power HIL simulation 73 FULL SCALE signals REDUCED SCALE power electronics electric machine emulation system mechanical power train process CONTROLLER BOARD (ECU) emulation Interest of the full-scale model: real parameters and non linearities are used can be used for full-scale HIL extension P A

60 Example of reduced-scale power HIL simulation 74 real bat. & chopper real machine T dcm emulation system reduced-power experimental set-up W gear speed / current loops drive W gear _ref T dcm_est P A mechanical trans. (4)-(6) ECU EMULATION CONTROLLER

61 Example of power adaptation 75 reduced-scale part full-scale part T dcm_est T dcm_mod emulation P A mechanical trans. (4)-(6) W gear _ref W gear _mod Tdcm mod ktt W gearmod kww dcmest gearref P em P mt emulation machine T full-scale mech. trans. P mt k T k W P PA = power amplification em reduced-scale mech. trans. k T T max k W W max W

62 76 Conclusion Full-scale HIL simulation Reduced-scale HIL simulation

63 Conclusion HIL simulation = Hardware (energy conversion) + Models computed in real-time in dynamic interactions 77 energetic model causal model dynamical model HARDWARE power Don t forget the coffee break! REAL-TIME SIMULATION an accurate and adapted model! an ideal interface system

64 159 References

65 Refrences from L2EP Univ. Lille1 160 [Allègre 10] A. L. Allègre, A. Bouscayrol, J. N. Verhille, P. Delarue, E. Chattot, S. El Fassi, Reduced-scale power Hardware-In-the-Loop simulation of an innovative subway", IEEE transactions on Industrial Electronics, vol. 57, no. 4, April 2010, pp (common paper of L2EP Lille and Siemens Transportation Systems). [Bouscayrol 06a] A. Bouscayrol, W. Lhomme, P. Delarue, B. Lemaire-S , S. Aksas, Hardware-in-the-loop simulation of electric vehicle traction systems using Energetic Macroscopic Representation, IEEE-IECON'06, Paris, November 2006, (common paper L2EP Lille and dspace France). [Bouscayrol 06b] A. Bouscayrol, X. Guillaud, R. Teodorescu, P. Delarue, W. Lhomme, Hardware-in-the-loop simulation of different wind turbines using Energetic Macroscopic Representation, IEEE-IECON'06, Paris, November 2006,, (common paper L2EP Lille and Aalborg university, Denmark). [Bouscayrol 09] A. Bouscayrol, X. Guillaud, P. Delarue, B. Lemaire-S , Energetic Macroscopic Representation and inversion-based illustrated on a wind energy conversion systems using Hardwarein-the-loop simulation, IEEE transaction on Industrial Electronics, [Bouscayrol 11] A. Bouscayrol, "Hardware-In-the-Loop simulation", Industrial Electronics Handbook, second edition, tome Control and mechatronics, Chapter 33, CRC Press, Chicago, March 2011, pp. 33-1/33-15, ISBN [Lhomme 07] W. Lhomme, R. Trigui, P. Delarue, A. Bouscayrol, B. jeanneret, F. Badin, Validation of clutch modeling for hybrid electric vehicle using Hardware-In-the-Loop simulation, IEEE-VPPC 07, Arlington (USA), September 2007, (common paper L2EP Lille and LTE INRETS Bron according to MEGEVH project). [Verhille 07] J. N. Verhille, A. Bouscayrol, P. J. Barre, J. P. Hautier, Validation of anti-slip for a subway traction system using Hardware-In-the-Loop simulation, IEEE-VPPC 07, Arlington (USA), September 2007, (common paper L2EP Lille and Siemens Transportation Systems). Special section «HIL simulation», IEEE transactions on Industrial Electronics, vol. 57, no. 4, April 2010.

66 Other refrences 161 [Athanasas 04] K. Athanasas, I. Dear, "Validation of complex vehicle systems of prototype vehicle", IEEE trans. on Vehicular Technology, Vol. 53, no. 6, November 2004, pp [Hanselmann 96] H. Hanselmann, "HIL simulation testing and its integration into a CACSD toolset", IEEE- CACSD 96, Dearborn, Sept. 96. [Kodjadi 04] H. M. Kojabadi, L. Chang, T. Boutot, "Development of a novel wind turbine simulator for wind energy conversion systems using an inverter-led induction motor", IEEE trans. on Energy Conversion, vol. 19, no. 3, pp , September [Li 06] H. Li, M. Steurer, S. Woodruff, K. L. Shi, "Development of a unified design, test, and research platform for wind energy systems based on hardware-in-the-loop real time simulation", IEEE trans. on Industrial Electronics, vol. 53, no. 4, June 2006, pp [Lok-Fu 07] P. Lok-Fu, V. Dinavahi, C. Gary, M. Steurer, P. F. Ribeiro, P.F., "Real-time digital time-varying harmonic modeling and simulation techniques IEEE Task Force on harmonics modeling and simulation", IEEE trans. on Power Delivery, Vol. 22, no. 2, April 2007, pp [Lu 07] B. Lu, X. Wu, H. Figueroa, A. Monti, "A low cost real-time hardware-in-the-loop testing approach of power electronics ", IEEE trans. on Industrial Electronics, vol. 54, no. 2, April 2007, pp [Maclay 97] D. Maclay, "Simulation gets into the loop", IEE Review, May 1997, pp [Rabbath 02] C. A. Rabbath, M. Abdoune, J. Belanger, K. Butts, Simulating hybrid dynamic systems, IEEE Robotics & Automation Magazine, Vol. 9, no. 2, June 2002, pp [Terwiech 99] P. Terwiesch, T. Keller, E. Scheiben, "Rail vehicle system integration testing using digital hardware-in-the-loop simulation', IEEE transactions on Control System Technology, Vol. 7, no. 3, May 99, pp [Zhang 01] Q. Zhang, J. F. Reid, D. Wu, "Hardware-in-the-loop simulator of an off-road vehicle electrohydraulic steering system", Trans. on ASAE, September 2001, pp

67 S. Astier, A. Bouscayrol, X. Roboam, "Introduction to Systemic Design", Systemic Design Methodologies for Electrical Energy, tome 1, Analysis, Synthesis and Management, Chapter 1, ISTE Willey editions, October 2012, ISBN: P. J. Barre, & al, "Inversion-based of electromechanical systems 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 systems", 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, 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 law synthesis", Studies in Informatics and Control Journal, vol. 13, no. 4, December 2004, pp H. Paynter, "Analysis and design of engineering systems", MIT Press, R. Zanasi, R. Morselli, "Modeling of Automotive Control Systems Using Power Oriented Graphs", IEEE-IECON'06, Paris, 162