Energetic Macroscopic Representation and Energy Management Strategy of a Hybrid Electric Locomotive

Transcription

1 Energetic Macroscopic Representation and Energy Management Strategy of a Hybrid Electric Locomotive J. Baert *, S. Jemei *, D. Chamagne *, D. Hissel *, D. Hegy ** and S. Hibon ** * University of Franche-Comte, FEMTO-ST (Energy Department), UMR CNRS 6174, Belfort, France. ** Alstom Transport, 3 Avenue des Trois Chênes, Belfort, France. jerome.baert@univ-fcomte.fr - samuel.hibon@transport.alstom.com 1

2 Summary 1. Introduction 2. Modeling of the Hybrid Electric Locomotive a) The batteries b) The ultra-capacitors c) The diesel driven generator set d) The global architecture 3. Energy Management Strategy 4. Conclusion and outlooks 2

3 Introduction Partners of the project Context and problematic 3

4 Introduction Adopted solution 60% less particles 40% less NO 15% less maintenance 4

5 Summary 1. Introduction 2. Modeling of the Hybrid Electric Locomotive a) The batteries b) The ultra-capacitors c) The diesel driven generator set d) The global architecture 3. Energy Management Strategy 4. Conclusion and outlooks 5

6 Modeling of the Hybrid Electric Locomotive The global architecture 6

7 Modeling of the Hybrid Electric Locomotive a) The batteries [1] The model takes into account: the voltage dynamics according to current variation, the polarization voltage to model the non linear variations of the OCV with the SOC, the exponential zone voltage to consider the NiCd hysteresis phenomenon. Discharging phase Charging phase [1] Olivier Tremblay and Louis-A. Dessaint Experimental Validation of a Battery Dynamic Model for EV Applications Worl d Electric Vehicle Journal Vol. 3 - ISSN AVERE 7

8 Modeling of the Hybrid Electric Locomotive a) The batteries - EMR 8

9 Modeling of the Hybrid Electric Locomotive a) The batteries - MCS 9

10 Modeling of the Hybrid Electric Locomotive a) The batteries - PCS 10

11 Modeling of the Hybrid Electric Locomotive b) The ultra-capacitors [2] [2] L. Zubieta and R. Bonert. Characterization of double-layer capacitors for power electronics applications. IEEE Transactions on Industry Applications, Vol. 36, No. 1, pp , jan/feb

12 Modeling of the Hybrid Electric Locomotive b) The ultra-capacitors 12

13 Modeling of the Hybrid Electric Locomotive c) The diesel driven generator set [3] Naturally aspirated diesel engine Salient pole synchronous machine [3] Baert, J., Jemei, S., Chamagne, D., Hissel, D., Hegy, D. and Hibon, S. (2012). Energetic Macroscopic Representation of a Naturally-Aspirated Engine coupled to a salient pole synchronous machine. PPPSC-IFAC,

14 Modeling of the Hybrid Electric Locomotive d) The global architecture [4] (5) (1) Diesel driven generator set (2) Batteries pack (3) Ultra-capacitors pack (4) Rheostat (5) Bus capacity (6) Energy Management Strategy (1) (4) (2) (3) (6) [4] J. Baert, S. Jemei, D. Chamagne, D. Hissel, S. Hibon, and D. Hegy, Practical Control Structure and Simulation of a Hybrid Electric Locomotive IEEE Vehicle Power and Propulsion Conference, VPPC

15 Summary 1. Introduction 2. Modeling of the Hybrid Electric Locomotive a) The batteries b) The ultra-capacitors c) The diesel driven generator set d) The global architecture 3. Energy Management Strategy 4. Conclusion and outlooks 15

16 Optimal fuzzy logic Energy Management Strategy Structure of the EMS Goal: To share the power required by the driving cycle performed by the locomotive between the different on-board sources, taking into account their own specifications. 16

17 Optimal fuzzy logic Energy Management Strategy Structure of the EMS Ultra-capacitors: Limitation of the State Of Charge (SOC) between 50% and 100%, control of the SOC according to the speed of the vehicle, supply the high frequencies of the power mission, 17

18 Optimal fuzzy logic Energy Management Strategy Structure of the EMS Batteries: Limitation of the SOC between 70% and 90%, control of the SOC according to the acceleration of the vehicle, supply the low frequencies of the power mission with the diesel driven generator set. 18

19 Optimal fuzzy logic Energy Management Strategy Structure of the EMS Diesel driven generator set: Use of a Fuzzy Logic Controller to determine the power delivered by this source, supply the low frequencies of the power mission with the batteries. IF AND THEN is N is P is P 19

20 Optimal fuzzy logic Energy Management Strategy Structure of the EMS 20

21 Optimal fuzzy logic Energy Management Strategy Results Powers distribution 21

22 Optimal fuzzy logic Energy Management Strategy Results Powers distribution (zoom) 22

23 Optimal fuzzy logic Energy Management Strategy Results Batteries SOC and acceleration 23

24 Optimal fuzzy logic Energy Management Strategy Results Ultra-capacitors SOC and speed 24

25 Summary 1. Introduction 2. Modeling of the Hybrid Electric Locomotive a) The batteries b) The ultra-capacitors c) The diesel driven generator set d) The global architecture 3. Energy Management Strategy 4. Conclusion and outlooks 25

26 Conclusion and outlooks Conclusion Development of the on-board sources dynamical models (EMR) with their control (MCS and PCS) Ultra-capacitors Batteries Diesel driven generator set Global architecture Fuzzy logic Energy Management Strategy: Optimization of the fuzzy logic controller parameters thanks to a genetic algorithm Frequency management of the sources Limitation of the secondary sources States Of Charges Outlooks Aging behavior characterization of the cells thanks to long term tests Improvement of the optimization process thanks to the Type-2 fuzzy logic 26

27 Thanks for your attention 27