Dr. Tony LETROUVE, Dr. Julien POUGET SNCF Innovation & Research Dep., MEGEVH network,

Transcription

1 EMR 15 Lille June 15 Summer School EMR 15 Energetic Macroscopic Representation Hardware-In In-the the-loop simulation : hybrid locomotive Energy Storage System behavior tests Dr. Tony LETROUVE, Dr. Julien POUGET SNCF Innovation & Research Dep., MEGEVH network,

2 - Outline - 1. HIL simulation interest and structuring problematic. Power HIL simulation of PLATHEE locomotive 3. Conclusion and outlooks

3 EMR 15 Lille June 15 Summer School EMR 15 Energetic Macroscopic Representation HIL simulation interest and structuring problematic

4 - Actual approach - Customer needs 4 Sizing and power flow studies Prototype elaboration Prototype development Prototype behavior validation Feasability response Direct validation of component behavior in real time on vehicle, Components homologation (hardware), All physics phenomenon are taken into account.

5 - Actual approach - Customer needs Time to market 5 Sizing and power flow studies Prototype elaboration Prototype development Prototype behavior validation Feasability response x x3 Cumulative dev. cost Sizing Prototype Complex to develop, more than one prototype needed, Time needed, The development Cost is exponential with the time on prototype, A lot of resources are needed (prototype, staffs and tracks availability), unrepeatable tests, Security and fault tolerance tests are made on-line.

6 - Actual approach - Customer needs Sizing and power flow studies Time to market 6 Prototype elaboration Prototype development Prototype behavior validation Feasability response Cumulative dev. cost Sizing Prototype Adding intermediary steps: Reduce the time on prototype (reduce the cost and time of development), Virtual homologation of some subsystems ahead of time. Solution : simulation?

7 - Adding simulation - Customer needs Sizing and power flow studies Simulation Time to market Component library development using EMR (common tool, formalism unification, easy to share, ) With Simulation Actual approach 7 Prototype elaboration Mise Prototype au point development du prototype Prototype behavior validation Cumulative dev. cost Feasability response Sizing Sim. Proto Prototype debugging ahead of time (ex. control), Easy to use, Quick development, Availability, Repeatable tests.

8 - Adding simulation - Customer needs Sizing and power flow studies Time to market Avec With Simulation Approche Actual approach initiale 8 Simulation Prototype elaboration Mise Prototype au point development du prototype Prototype behavior validation Cumulative dev. cost Feasability response Sizing Sim. Proto Models validity range, virtual homologation complicated, real time portability of the control?

9 - Adding simulation - Customer needs Sizing and power flow studies Time to market Avec With Simulation Approche Actual approach initiale 9 Simulation Prototype elaboration Mise Prototype au point development du prototype Prototype behavior validation Cumulative dev. cost Feasability response Sizing Sim. Proto Solution: «SuperModel» development? How many development time? All interaction are they taken into account?

10 - Battery test example - 1 voltage Battery + PE current Upstream system Control & Energy management ageing? temperature? EMI? Etc. Development time? Computation time?

11 - Battery test example - No more model dependency : real power part + - I N T E R F A C E voltage current Upstream system 11 Control & Energy management

12 - HIL simulation - 1 Simulation Signal HIL Simulation Power HIL Simulation Prototype Power Power Power Power Control Control Control Control Emulated Software Real components Hardware

13 - HIL simulation benefits - Customer needs Time to market With simulation Actual approach With HIL 13 Sizing and power flow studies Simulation Control development Simulation HIL Prototype behavior validation Feasability response RT control validation and power subsystems validation Cumul dev. cost Siz. Sim. HIL Proto Reduce development time, Financial benefits (mobilization et component deterioration), Security et quality tests (fault tolerance tests), Repeatable tests, Virtual homologation available.

14 - Structuring needs problematic of a Power HILs - Power adaptations? (Signal) + - I N T E R F A C E Measures (Power) (Signal) Voltage Current Upstream system 14 Studied system (Power) Control & Energy management Interface (Power and Signal) Control (signal) Can EMR helps to structure the different parts of a HIL simulation? Emulated models (signal)

15 EMR 15 Lille June 15 Summer School EMR 15 Energetic Macroscopic Representation Power HIL simulation of PLATHEE locomotive

16 - BB635 Diesel Electric locomotive hybridization - DC Bus DCM 4*1 kw Traction Wh. 16 Aux. Generator Mth 6 kw SM Drawbacks : - No energetic storage for traction or auxiliairies, - Diesel engine is uninterrupted (Auxilairies, etc.), - Diesel engine is not always in its maximal efficiency point.

17 SC 8x Scaps (6,94 kwh) «HIL simulation : hybrid locomotive ESS behavior tests» - PLATHEE - Power HIL simulation objective - Storage system DC Bus DCM *1 kw Traction Wh. 17 Bat 4x9 NiCd batt.(194 kwh) Generator Aux. Mth 15 kw SM Energy management strategy Objectifs : Defining a structured experiment for Energy storage tests, Validation of the real time portability of the developed control and EMS, Subsystem tests (nominal and fault tolerance) in a controlled environment before full prototype implementation.

18 - PLATHEE - Power HIL simulation objective - Storage system DC Bus Traction 18 Generator Energy management strategy Objectifs : Defining a structured experiment for Energy storage tests, Validation of the real time portability of the developed control and EMS, Subsystem tests (nominal and fault tolerance) in a controlled environment before full prototype implementation.

19 - Power HIL simulation structure - SCs u sc tot v ch m ch. 8 c DC u C u C i hach m ch u hach i arm i arm e mach C mcc Ω red C roue F tot Ω roue Brak. F roue v F train freins F tract F res 19 Env Bat u bt tot 4 v ch m ch. i bt DC i tot i aux Aux F freins-ref ICE C mth Ω arb Ω arb C ms i ms u hach_ref C roue_ref F roue_ref F tract_ref F tot_ref i arm_ref C mcc_ref C mth_ref Ω arb_ref C mth_ref C ms_ref Generator Strategy Driving Strategy k D v ch_ref 4 P ge_ref SC 1 6 Scaps (6,94 kwh) DC Bus DCM *1 kw Wh. _ref _ref i bt DC_ref Bat 1 16 NiCd batt. (194 kwh) Aux. v ch_ref _ref 8 _ref c DC_ref EMS ICE SM 15 kw Energy managment strategy

20 System under test «HIL simulation : hybrid locomotive ESS behavior tests» - Power HIL simulation structure - SCs Bat u sc tot u bt tot v ch m ch. 8 v ch m ch. 4 c DC i bt DC i tot i aux u C Aux u C i hach m ch u hach i arm i arm e mach C mcc Ω red C roue F tot Ω roue Brak. F roue v F train freins F freins-ref F tract F res Env ICE C mth Ω arb Ω arb C ms i ms u hach_ref C roue_ref F roue_ref F tract_ref F tot_ref i arm_ref C mcc_ref C mth_ref Ω arb_ref C mth_ref C ms_ref Generator Strategy Driving Strategy k D v ch_ref 4 P ge_ref SC 1 6 Scaps (6,94 kwh) DC Bus DCM *1 kw Wh. _ref _ref i bt DC_ref Bat 1 16 NiCd batt. (194 kwh) Aux. v ch_ref _ref 8 _ref c DC_ref EMS ICE 15 kw SM Energy management strategy

21 System under test «HIL simulation : hybrid locomotive ESS behavior tests» - Power HIL simulation structure - SCs Bat u sc tot u bt tot v ch m ch. 8 v ch m ch. 4 c DC i bt DC i tot i aux u C Aux u C i hach m ch u hach i arm i arm e mach C mcc Ω red C roue F tot Ω roue Brak. F roue v F train freins F freins-ref F tract F res 1 Env ICE C mth Ω arb Ω arb C ms i ms u hach_ref C roue_ref F roue_ref F tract_ref F tot_ref i arm_ref C mcc_ref C mth_ref Ω arb_ref C mth_ref C ms_ref Generator Strategy Driving Strategy k D P ge_ref v ch_ref 4 _ref _ref i bt DC_ref v ch_ref 8 _ref _ref c DC_ref EMS

22 System under test «HIL simulation : hybrid locomotive ESS behavior tests» - Power HIL simulation structure - SCs Bat u sc tot u bt tot v ch v ch m ch. m ch. 8 4 c DC i bt DC i tot m ch h i l i l u source SE Powertrain Interface System Generator Interface System SE i l u source i l-ref h i l h-ref i ms m ch -ref h-ref i l-ref u C u C i hach m ch u hach i arm i arm e mach C mcc Ω red C roue Ω roue Brak. F roue v F train freins F tract F tot F res Env ICE C mth Ω arb Ω arb C ms -ref i aux Aux u hach_ref C roue_ref F roue_ref F tract_ref F tot_ref i arm_ref C mcc_ref F freins-ref C mth_ref Ω arb_ref C mth_ref C ms_ref Generator Strategy Driving Strategy k D P ge_ref v ch_ref 4 _ref _ref i bt DC_ref v ch_ref 8 _ref _ref c DC_ref EMS

23 System under test «HIL simulation : hybrid locomotive ESS behavior tests» - Power HIL simulation structure - SCs Bat u sc tot u bt tot v ch v ch m ch. m ch. 8 4 c DC i bt DC i tot m ch h i l i l u source SE 3 Experimental test bed h-ref SE i l u source i l-ref h i l h-ref i ms m ch -ref i l-ref u C u C i hach m ch u hach i arm i arm e mach C mcc Ω red C roue Ω roue Brak. F roue v F train freins F tract F tot F res Env Real-time simulator ICE C mth Ω arb Ω arb C ms C ms_ref C mth_ref Ω arb_ref C mth_ref -ref Generator Strategy i aux Aux u hach_ref C roue_ref F roue_ref F tract_ref F tot_ref i arm_ref C mcc_ref F freins-ref Driving Strategy k D P ge_ref v ch_ref _ref _ref 4 i bt DC_ref Reduced-scale Power adaptation element v ch_ref 8 _ref _ref c DC_ref EMS

24 1 «HIL simulation : hybrid locomotive ESS behavior tests» - Experimental setup and results - 1 Same EMS than Prototype : Models validation Power Electronics SEMIKRON x OP56 real-time simulator v loc 1 [km/h] 5 [A] (f) (a) -5 Reference -1 Measure t(s) t(s) 6 P tract 5 [kw] (b) P aux [kw] (c) P gs [kw] (d) Cons [L] (e) i bat U bat [V] (g) c [A] U bus [V] (h) Reference Measure U sc [V] (i) (j) Reference Measure 48v Battery pack 48v Maxwell Supercaps 4W controllable voltage source 4

25 - Experimental setup and results - New EMS and studies outlooks : Power Electronics SEMIKRON Fair strategies comparison (maintenance, x OP56 component behavior, fuel, ) real-time simulator 1 bat 8 1 i bat v loc [km/h] (a) P tract [kw] (b) P aux [kw] P gs (c) [kw] (d) t(s) 1 3 Cons [L] (e) [A] [A] (f) Reference Measure t(s) U bat [V] SoC(g) bat [%] c [A] U bus [V] c (h) [A] Reference Measure 1 3 U sc [V] SoC (i) sc [%] 1 3 (j) Reference Measure v Battery pack 48v Maxwell Supercaps 4W controllable voltage source 5

26 EMR 15 Lille June 15 Summer School EMR 15 Energetic Macroscopic Representation Conclusion and outlooks

27 - Conclusion & outlooks - EMR as a structuring tool : 7 - Such a complex system and experiment needs methodology : EMR, - Integral causality allows to use description and control part in real time. Reduced-scale Power HIL simulation - Reduce the cost and time to market of new developments, - Do not required any prototype component, - Quick development and adjustment possibility, - Interface systems behavior validation, - Prepare experiment for full-scale. PLATHEE Supercapacitors Outlooks - fault tolerance tests and control robustness, - full-scale HIL simulation, - implementation on prototype. PLATHEE NiCd Batteries

28 EMR 15 Lille June 15 Summer School EMR 15 Energetic Macroscopic Representation Thanks for your attention! Tony LETROUVE Julien POUGET

29 - Authors - 9 Dr. Julien POUGET SNCF, Innovation & Research Dept., MEGEVH, France PhD in Electrical Engineering at University of Franche-Comte, Belfort Research topics: optimal design, modeling, control and energy management applied in railway hybrid energy systems (electrical and diesel locomotive, electrical and thermal building and railway network) Dr. Tony LETROUVE SNCF, Innovation & Research Dept., MEGEVH, France PhD in Electrical Engineering at University of Lille & PSA (13) Research topics: EMR, HIL simulation, Energy Management, Prototyping