DISTRIBUTION AND STRATEGY

Transcription

1 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» «ENERGY DISTRIBUTION AND STRATEGY» Prof. A. Bouscayrol (University Lille1, L2EP, MEGEVH, France) based on the course of Master Electrical Engineering & sustainable Development University Lille1 Aalto University

2 Parallel HEV «Energy Distribution and Strategy» - Objective: example of HEV control - BAT VSI Fuel EM ICE Trans. 2 fast subsystem controls EM control ICE control Trans control slow system supervision Energy management (supervision/strategy) driver request

3 Parallel HEV «Energy Distribution and Strategy» BAT - Different control levels (2) - VSI1 Fuel EM1 ICE EMR Trans. 3 fast subsystem controls EM1 control ICE control Trans control Inversion-based control slow system supervision Energy management (supervision/strategy) How to manage energy? Interaction between both levels? driver request

4 - Outline Control decomposition Local control structure Strategy level for energy management 2. Various inversions of coupling elements Different kinds of energy management Inversion of the different cases 3. Analysis and strategy Analysis of the system possibilities Strategy level 4. Application to the automatic subway VAL 206

5 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 1. «Local control and energy management» Aalto University

6 - Principle of Inversion-based methodology - 6 cause input System effect output measurements? right cause Control desired effect control = inversion of the causal path 1. Which algorithm? (how many controllers) 2. Which variables to measure? 3. How to tune controllers? 4. How to implement the control? Inversion-based methodology automatic control industrial electronics

7 - EMR and Inversion-based methodology - 7 cause effect input SS 1 SS 2 SS n output measure? measure? measure? right cause C 1 C 2 C n desired effect EMR = system decomposition in basic energetic subsystems (SSs) Remember, divide and conquer! Inversion-based control: systematic inversion of each subsystems using open-loop or closed-loop control

8 - Mirror effect - 8 cause SS 1 SS 2 SS n effect right cause C 1 C 2 C n desired effect The control scheme is developed as a mirror of the model

9 Legend - Inversion of EMR elements - conversion element direct inversion + disturbance rejection 9 Control = light blue Parallelograms with dark blue contour direct inversion accumulation element controller + disturbance rejection indirect inversion sensor mandatory link facultative link coupling element distribution criteria

10 - Inversion-based methodology EMR of the system 2. Tuning path 3. Inversion step-by-step Strong assumption: all variables can be measured! SE SM 4. Simplification of the control scheme 5. Estimation of non-measured variable Strategy 6. Tuning of controllers 7. Strategy

11 - Strategy and coupling elements - 11 v ES MS v ref Strategy

12 - Different control levels - 12 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 Quasi-static models Dynamic and causal models [Delarue & al 2005] compatibility of the control levels compatibility in term of inputs/outputs

13 - Articulation of control levels - 13 Local control: Fast energy management in each subsystem Objective: ensure the best efficiency of each component in function of the request Inversion of each element, step-by-step, using dynamic causal models Energy management: Coordination of energy between all subsystems Objective: ensure the best energy distribution in function of the global demand Global view for decision using quasi-static or static models Could be considered as an inversion of a global model of the system

14 BAT VSI - Articulation of control & models - EM 14 Fuel ICE Trans. Inversion of causal dynamical models EM control ICE control Trans control Strategy delivers references for local controls Energy management (supervision/strategy) driver request Inversion of a global static model

15 inverter - From dynamical model of IM drive - stator EM windings conversion Park s transformation 15 V DC u d/s inv v s-dq i s-dq i vsi i im i s-dq e s-dq i s-dq-est rd Global behavior of the drive i sd (machine + inverter + control) r-est T im gear e s-dq-est i sd-ref d/s_est r-ref u inv-ref v s-dq-ref i s-dq-ref T im-ref

16 V DC drive - to static and dynamical models - T im T im (Nm) Efficiency map 16 i vsi gear T im-ref gear (rad/s) V DC T im static model i vsi x + - x gear T im-ref

17 - Coherence of dynamical and static models - 17 Static model: no dynamical effect, I/O could be changed V DC T im V DC gear V DC gear i vsi gear i vsi T im T im Tim-ref gear-ref static V DC i vsi backward dynamic T im What happens if EM = inversion of a static model and IBC = inversion of dynamical models with different I/O? Bad articulation between control levels i vsi Tim-ref gear

18 Rule-based «Energy Distribution and Strategy» - Energy management of HEVs - deterministic rule-based fuzzy rule-based state machine / power follower/ thermostat control predictive / adaptive / conventional 18 Optimization based global optimization real-time optimization Dynamic programming / stochastic DP / Game theory / Optimal control. Robust control / Model predictive / decoupling control / l control Energy management (supervision/strategy) [Salmasi 2007] driver request

19 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 2. «Inversion of various coupling elements» Aalto University

20 - Upstream coupling elements - upstream common part Example: differential 20 u 1 y 1 y 21 u 21 diff T gear T ldiff lwh T rdiff rwh Tldif wh T rdif rwh Tdiff 2 2 lwh y 2p u 1p Tldiff m: number of upstream power flows p: number of downstream power flows T diff wh lwh T rdiff m < p objective = distribution of energy into p different power flows rwh m=1, p=2 (m<p) objective = distribution of torque

21 - Downstream coupling elements - downstream common part Example: chassis of a train 21 y 21 u 21 y 2 4 traction boggies y 2p u 1m u 2 F bog1 F bog2 v train F tot m: number of upstream power flows p: number of downstream power flows F bog3 F bog4 v train v train v train v train m > p objective = collect energy into m different power flows m=4, p=1 (m>p) objective = collecting bogie forces

22 - Neutral coupling elements - 22 u 11 y 11 y 21 u 21 Example: Park s transformation d/s u 13 i s1 u 23 v sd i sd v sq u 1m y 1m y 21 u 21 i s2 i sq m: number of upstream power flows p: number of downstream power flows m = p objective = reorganize power flows m=2, p=2 (m=p) objective = convert AC voltages and currents into DC voltages and currents

23 - Inversion of upstream coupling elements - 23 y 21 u 21 Example: differential u 1 T ldiff y 1 y 2p u 1p T gear wh lwh T rdiff y 21-ref rwh u 1 k W1 k W(m-p) y 2p-ref T gear no measurement no controller (m- p) weighting variables k W T diff-ref1 T diff-ref2 u1... kw1 y11ref kwp y1 pref T gear 2 kwtdiff ref 1 (1 kw) Tdiff ref 2

24 u 11 y 11 «Energy Distribution and Strategy» - Inversion of downstream coupling elements (1) - case 1: all inputs are used F bog1 Example: chassis of a train 24 y 2 v train F bog2 F tot u 1m y 1m u 2 F bog3 v train v train v train u 11 u 1m k D1 k D(m-p) no measurement no controller (m- p) distribution variables y 2p-ref u u 11 1m k k D1... Dm y 2ref y 2ref F bog4 F bog1 F bog2 F bog3 F bog4 v train k D1 k D2 F tot-ref k D3

25 - Inversion of downstream coupling elements (2) - case 2: not all inputs are used u 11 y 11 F bog1 Example: chassis of a train 25 u 1m y 1m y 2 u 2 only 2 driven boggies F bog2 F bog3 v train v train v train F tot v train F bog4 u 1m-meas v train F bog2-meas F bog1 F bog3-meas u 11 y 2p-ref F bog4 F tot-ref measurement of non-used inputs no controller k D1

26 - Inversion of neutral coupling elements - 26 u 11 y 11 u 21 y 21 Example: Park s transformation d/s u 1m y 1m u 21 y 21 u 13 i s1 u 23 i s2 v sd i sd v sq d/s i sq u 11 y 21-ref u 13-ref v sd-ref u 1p y 2p-ref u 23-ref v sq-ref no measurement no controller / direct inversion use of the inverse matrix

27 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 3. «Analysis of the system possibilities and strategy level» Aalto University

28 - Critical factors - 28 n O = number of objectives Example: 3-leg Voltage-Source-Inverter i 1 n C = number of constraints (in order to achieve the objectives) V DC s 11 s 12 s 13 i 2 u 13 n T = number of tuning variables (in order to act on the system) s 21 s 22 s 23 i vsi n O = 2 (u 13 and u 23 ) u 23 n C = 3 (3 commutation cells) S i 1 S i 2 for i 1,2,3 n T = 6 (6 switching orders S ij )

29 - Ideal case - 29 n T n O n C They are enough tuning inputs to achieve the objectives and realize the constraints Example: 3-phase induction machine Park s transformation u d/s inv i im stator windings v s-dq i s-dq i s-dq e s-dq EM conversion T im rd n O = 1 (T im ) i sd gear n T n O n C n C = 1 (flux r ) n T = 2 (u 13 and u 23 ) Field-oriented control is a way to impose flux and torque by voltages (using a decoupling (d,q) frame)

30 - Optimisation case - 30 n T n O n C Example: 3-leg Voltage-Source-Inverter i 1 They are more tuning inputs than the objectives and the constraints V DC s 11 s 21 s 12 s 22 s 13 s 23 i 2 u 23 u 13 i vsi all tuning inputs must be used the degrees of freedom can be used for Optimisation a strategy level is required to define the degrees of freedom n O = 2 (u 13 and u 23 ) n C = 3 (3 commutation cells) n C = 6 (6 switching orders S ij ) Various optimization strategies for VSI such as 3 rd harmonic injection, flat-top modulation

31 - Compromise case - 31 n T n O n C Example: differential T gear T ldiff lwh They are not enough tuning inputs than the objective and the constraints wh T rdiff rwh a compromise must be defined (priorities) a strategy level is required to define the priority T gear k W n O = 2 (T diff1 and T diff1 ) n C = 0 n C = 1 (T gear ) T diff-ref1 T diff-ref2 Ex: k W =1 priority to T diff1

32 - Coupling elements and strategy - 32 All downstream and upstream coupling elements Example: differential T gear T ldiff lwh require criteria (distribution or weighting) wh T rdiff rwh these criteria variables must be defined by the strategy level T gear k W T diff-ref1 T diff-ref2 Strategy Ex: during straight lines, T gear = average value of both requests

33 - Strategy level - 33 Strategy level: global management of the whole system has to define: local control references distribution coefficients weighting coefficients optimization inputs compromises For energetic system: definition of priority between performances and efficiency Inversion of a global static model (different possibilities) Example: Flux weakening in EVs U U max rated U depends on the battery voltage V bat depends on velocity v EV ref static plots global view V bat-meas v EV-meas

34 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 4. «Application to the control of an automatic subway» part I: simplified system Prof. A. Bouscayrol (University Lille1, L2EP, MEGEVH, France) Aalto University based on PhD of J. N. Verhille in collaboration with Siemens Transportation Systems

35 - Example of VAL automatic Subway - Traction systems of the subway VAL VAL VAL Actual system (4 DC machines + 6 choppers) 1 vehicle = 2 car, 1 car = 2 bogies 1 bogie = 1 DC machine with field winding 1 chopper for each field winding 1 chopper for the armature wining in series

36 - Example of VAL automatic Subway - Traction systems of the subway VAL VAL Studied system (2 DC machines + 1 chopper) 1 vehicle = 1 car avec 2 bogies 1 bogie = 1 DC machine with permanent magnets 1 4 quadrants chopper for the DC machines in series

37 - Example of VAL automatic Subway - 1. EMR of the System 37 chopper Rail U DC i Hi u Hi u i Hi Hi m m Hi Hi U i DC ind m Hi

38 - Example of VAL automatic Subway - 1. EMR of the System 38 chopper DC machines in series Rail U DC u Hi e mcc1 u Hi L 1 e mcc1 i Hi m Hi e tot L 2 e mcc2 u Hi (L L 1 2 ) d dt ind L 1 +L 2 equivalent inductance i e tot i1 i1 i etot e ind mcc1 e mcc2 series connection

39 - Example of VAL automatic Subway - 1. EMR of the System 39 chopper DC machines in series C mcc1 Rail U DC i Hi u Hi e mcc1 bog1 e tot m Hi C e mcc mcc1 1 k i k ind bog1

40 - Example of VAL automatic Subway - 1. EMR of the System 40 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC u Hi e mcc1 bog1 v rame F tot i Hi e tot v rame m Hi F bog1 bog1 k k bog bog C v mcc1 rame F tot F v v 1 bog 2 1 F v rame bog2

41 - Example of VAL automatic Subway - 1. EMR of the System 41 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame M d dt v rame F tot - F res

42 - Example of VAL automatic Subway - 2. Tuning path of the System 42 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame n T =1 (m Hi ) n O =1 (V rame ) n C =0

43 - Example of VAL automatic Subway - 3. MCS of the System 43 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes Distribution of traction forces F bog1-ref =k R F tot -ref F bog2-ref =(1-k R )F tot -ref F bog1-ref F tot-ref v rame-ref Velocity controller k R

44 - Example of VAL automatic Subway - 3. MCS of the System 44 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi Weighting of the currents e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes -ref =k P -ref1 + (1-k P ) -ref2 -ref1 -ref F bog1-ref F tot-ref v rame-ref k P C mcc1-ref k R

45 - Example of VAL automatic Subway - 3. MCS of the System 45 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes -ref1 u Hi-ref -ref F bog1-ref F tot-ref v rame-ref Current controller k P C mcc1-ref k R

46 - Example of VAL automatic Subway - 3b. Strategy of the System 46 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes -ref1 u Hi-ref -ref F bog1-ref F tot-ref v rame-ref k P C mcc1-ref k R strategy

47 - Example of VAL automatic Subway - 4. Simplification of the control 47 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes -ref1 u Hi-ref -ref F bog1-ref F tot-ref v rame-ref k P =1, master slave control k P C mcc1-ref k R Strategy

48 - Example of VAL automatic Subway - 4. Simplification of the control 48 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi k R =1/2, equi-distribution F tot v rame v rame-mes u Hi-ref -ref F bog1-ref F tot-ref v rame-ref C mcc1-ref k R Strategy

49 - Example of VAL automatic Subway - 4. Simplification of the control 49 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes u Hi-ref -ref F bog1-ref C mcc1-ref 1/2 F tot-ref v rame-ref

50 - Example of VAL automatic Subway - 4. Simplification of the control 50 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes Bloc merging u Hi-ref -ref 1/2 F tot-ref v rame-ref

51 - Example of VAL automatic Subway - 4. Simplification of the control 51 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes u Hi-ref -ref Simplification of compensations 1/2 F tot-ref v rame-ref

52 - Example of VAL automatic Subway - 5. Estimation of non-measured variables 52 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 e tot F Env v rame res. m Hi Velocity estimation bog1 v rame F tot v rame v rame-mes u Hi-ref -ref v rame-est = k bog2 1/2 F tot-ref v rame-ref

53 - Example of VAL automatic Subway - 53 chopper DC machines in series bogies vehicle C mcc1 F bog1 Rail U DC i Hi u Hi e mcc1 bog1 v rame e tot F Env v rame res. m Hi F tot v rame v rame-mes u Hi-ref simplifications -ref limitations of performances 1/2 F tot-ref v rame-ref

54 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 4. «Application to the control of an automatic subway» part II: real system Prof. A. Bouscayrol (University Lille1, L2EP, MEGEVH, France) Aalto University Based on paper presented at IEEE-VPPC 06 in collaboration with Siemens Transportation Systems

55 - EMR of electrical part - 55 rail filter parallel choppers MCC in series bogies u filter i field1 T mach1 i arm Seq1 ES V DC i filter u filter u filter u chop2 i arm e arm1 bog1 i filter u filter i tot u filter i arm m chop2 e tot Seq2

56 - Control of electrical part - 56 rail filter parallel choppers MCC in series bogies u filter i field1 T mach1 i arm Seq1 ES V DC i filter u filter u filter u chop2 i arm e arm1 bog1 i filter u filter i tot u filter i arm m chop2 e tot Seq2 u filter-mes i field2-ref i arm-ref =k W i arm-ref1 +(1-k W )i arm-ref2 u chop3-ref u chop2-ref i arm-ref i arm-ref2 i arm-ref1 T mach2-ref T mach1-ref u chop1-ref i field1-ref

57 - Control of electrical part - 57 rail filter parallel choppers MCC in series bogies u filter i field1 T mach1 i arm Seq1 ES V DC i filter u filter u filter u chop2 i arm e arm1 bog1 i filter u filter i tot u filter i arm m chop2 e tot Seq2 u filter-mes i field2-ref Strategy has to define the 3 criteria u chop3-ref u chop2-ref i arm-ref i arm-ref2 i arm-ref1 T mach2-ref T mach1-ref u chop1-ref i field1-ref

58 rail filter parallel - Control of electrical part - choppers MCC in series bogies 58 ES V DC T mach1 bog1 Seq1 Seq2 u filter-mes i field2-ref u chop3-ref u chop2-ref u chop1-ref i arm-ref i field1-ref i arm-ref2 T i mach2-ref arm-ref2 arm-ref1 Actual control: no possibility of independent T mach1-ref torque

59 motor - EMR of mechanical part - differential brake gearbox wheels contact chassis environ. 59 T dif1 dis1 C red1 red1 v roue1 F cont1 T mach1 arb T dif disf1 T red1 T roue1 F cont1 red1 v VAL F bog1 v VAL DCM SM arb T red pont T dif2 dis2 C red2 red2 v roue2 F cont2 v VAL F res motor MOTEUR TRANSMISSION PONT + DIFFERENTIEL disf2 T red2 T roue2 F cont2 red2 v VAL non-linear devices 1/2 ESSIEU 1/2 ESSIEU PNEU REDUCTEUR REDUCTEUR PNEU T red backslash F slip

60 - Control of mechanical part - 60 DCM1 DCM2 T mach2ref v VAL-ref T mach1ref

61 - Control of mechanical part - 61 DCM1 DCM2 T mcc2-ref Master-slave control v rame-ref T mach1ref

62 - Actual control of mechanical part - 62 DCM1 DCM2 arb-mes v rame-est Merging of control blocs T mach1ref T mach1ref Actual control: no local management of anti-slip v rame-ref

63 - Simulation model - Matlab/Simulink TM electrical part mechanical part 63 Actual control

64 - Validation model (1) - 64 experimental simulation armature current (A) field current (A) experimental simulation

65 Test at normal operating - Validation model (2) - experimental simulation Test at maximal torque velocity (m/s) 65 velocity (m/s) experimental simulation

66 Aalto University Finland May 2011 «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» 4. «Application to the control of an automatic subway» part III: anti-slip strategy Prof. A. Bouscayrol (University Lille1, L2EP, MEGEVH, France) Aalto University Based on paper presented at IEEE-VPPC 07 in collaboration with Siemens Transportation Systems

67 - VAL 206 and control - 67 VAL Automatic Subway: Lille, Paris airport, Chicago, Taïpeh... Actual control VAL 206 identical torque for 4 motors global anti-slip (cancellation of torque) 4-mes T ref v ref T 1-ref 1-mes T 2-ref 2-mes T 3-ref 3-mes T 4-ref 4-mes? v ref STS Independent controls with same power structure? Performances with local anti-slip?

68 Tdcm_ref wh22_mes wh21_mes wh12_mes wh11_mes strategy - Anti-slip control - v sub_mes F tot1_ref v sub_ref Actual control: slip detection 68 Torque set to zero T dcm_ref F bog_ref shaft2_mes T dcm2_ref shaft2_ref wh2_ref k W2 k D2 F bog2_ref v sub_mes New strategy: slip detection wh22_mes wh21_mes wh12_mes wh11_mes new strategy k D F tot1_ref v sub_ref Reduction of torque of the slipping wheel T dcm1_ref shaft1_mes shaft1_ref wh1_ref k W1 k D1 F bog1_ref Increase of other torques

69 - Philosophy of the strategy - 69 F F Normal operation: equal distribution of traction forces 1 kd kd1 kd2 kw1 kw 2 2 Bog1 tot F Bog2 FBog i F Bog3 F Bog4 1 4 F tot k W2 k D2 Slipping on bogie 1: cancelation of F bog1 and new distribution of other forces k k k D D2 D1 1 2 k k W 2 W1 1 0 wh22_mes wh21_mes wh12_mes wh11_mes new strategy k W1 k D1 k D F F F tot Bog1 Bog2 0 F Bog3 F Bog i F Bog4 1 3 F tot

70 - Simulation results - Loss of adhesion of wheel no actual control velocity (m/s) New anti-slip strategy velocity (m/s) v sub_ref v sub v sub_ref v sub traction force (Nm) F tot (Nm) traction force (Nm)

71 - HIL simulation of the VAL traction system - 71 traction drive T im mechanical AC load drive power train drive control T im ref = mod mechanical power train drive control power train control T im-ref v ev-ref power control model

72 - Experimental results - 72 current (A) i arm velocities (m/s) i field2 current (A) v sub_ref v sub i field1 Loss of adhesion on wheel 1 F bog1 is decreased by acting on i field1 F bog2 is increased by acting on i arm

73 -Conclusion- 73 New anti-slip control Energetic Macroscopic Representation of VAL traction Inversion-based control from EMR Best repartition of traction efforts Best performances during slipping phenomena HIL simulation real-time validation of the control dual drive system to be implemented on the actual system

74 Aalto University Finland May 2011 Aalto University «Energy Management of EVs & HEVs using Energetic Macroscopic Representation» «Conclusion» Inversion based control = inversion of EMR inversion of dynamic causal models a unique Maximum Control Scheme Strategy Level = inversion of a global static model global model and local dynamic models must have same I/O different strategies are possible Coupling elements highlight the degrees of freedom, which must be defined in the strategy level Efficient energy management of EVs and HEVs well-defined local controls of subsystems coherent articulation between control levels efficient strategy level

75 - References - A. Bouscayrol, B. Davat, B. de Fornel, B. François, J. P. Hautier, F. Meibody-Tabar, E. Monmasson, M. Pietrzak-David, H. Razik, E. S , M. F. Benkhoris, "Control Structures for Multi-machine Multi-converter Systems with upstream coupling", Mathematics and Computers in Simulation, vol. 63, no. 3-5, pp , November 2003 (common paper of GE 44 St Nazaire, GREEN Nancy, L2EP Lille, LEEI Toulouse and LESiR- SATIE Cachan, according to the MMS project of the GDR-ME2MS) A. Bouscayrol, M. Pietrzak-David, P. Delarue, R. Peña-Eguiluz, P. E. Vidal, X. Kestelyn, Weighted control of traction drives with parallel-connected AC machines, IEEE Transactions on Industrial Electronics, December 2006, vol. 53, no. 6, p (common paper of L2EP Lille and LEEI Toulouse). 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 (common paper L2EP Lille and Jeumont SA). J. N. Verhille, A. Bouscayrol, P. J. Barre, J. P. Hautier, " Model validation of the whole traction system of an automatic subway, IEEE-VPPC'06, Windsord (UK), September 2006 (common paper of L2EP Lille and Siemens TS) J. N. Verhille, A. Bouscayrol, P. J. Barre, J. P. Hautier, Validation of anti-slip control 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 System) J. N. Verhille, "Représentation Énergétique Macroscopique du métro VAL 206 et structures de commande déduites par inversion", (text in French), PhD report, ENSAM, France, July