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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,
90010 Belfort, France.** Alstom Transport, 3 Avenue des Trois Chênes, 90000 Belfort, France.
Summary
1. Introduction
2. Modeling of the Hybrid Electric Locomotivea) The batteries
b) The ultra-capacitors
c) The diesel driven generator set
d) The global architecture
3. Energy Management Strategy
4. Conclusion and outlooks
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Partners of the project
3
Introduction
Context and problematic
Introduction
4
Adopted solution
• 60% less particles
• 40% less NO
• 15% less maintenance
Summary
1. Introduction
2. Modeling of the Hybrid Electric Locomotivea) 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
Modeling of the Hybrid Electric Locomotive
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The global architecture
Modeling of the Hybrid Electric Locomotive
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[1] Olivier Tremblay and Louis-A. Dessaint Experimental Validation of a Battery Dynamic Model for EV Applications World Electric Vehicle Journal Vol. 3 - ISSN 2032-6653 - © 2009 AVERE
Discharging phase
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.
Charging phase
a) The batteries [1]
Modeling of the Hybrid Electric Locomotive
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a) The batteries - EMR
Modeling of the Hybrid Electric Locomotive
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a) The batteries - MCS
Modeling of the Hybrid Electric Locomotive
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a) The batteries - PCS
Modeling of the Hybrid Electric Locomotive
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[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. 199 205, jan/feb 2000.
b) The ultra-capacitors [2]
Modeling of the Hybrid Electric Locomotive
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b) The ultra-capacitors
Modeling of the Hybrid Electric Locomotive
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c) The diesel driven generator set [3]
[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, 2012.
Naturally aspirated diesel engine Salient pole synchronous machine
Modeling of the Hybrid Electric Locomotive
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(1) Diesel driven
generator set
(2) Batteries’ pack
(3) Ultra-capacitors’
pack
(4) Rheostat
(5) Bus capacity
(6) Energy Management
Strategy
(1)
(2) (3)
(4)
(5)
(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, 2012. VPPC ’12.
d) The global architecture [4]
Summary
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1. Introduction
2. Modeling of the Hybrid Electric Locomotivea) The batteries
b) The ultra-capacitors
c) The diesel driven generator set
d) The global architecture
3. Energy Management Strategy
4. Conclusion and outlooks
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Structure of the EMS
Optimal fuzzy logic Energy Management Strategy
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.
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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,
Optimal fuzzy logic Energy Management Strategy
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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.
Optimal fuzzy logic Energy Management Strategy
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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 is N
AND is P
THEN is P
Optimal fuzzy logic Energy Management Strategy
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Structure of the EMS
Optimal fuzzy logic Energy Management Strategy
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Results – Powers distribution
Optimal fuzzy logic Energy Management Strategy
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Results – Powers distribution (zoom)
Optimal fuzzy logic Energy Management Strategy
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Results – Batteries’ SOC and acceleration
Optimal fuzzy logic Energy Management Strategy
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Results – Ultra-capacitors’ SOC and speed
Optimal fuzzy logic Energy Management Strategy
Summary
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1. Introduction
2. Modeling of the Hybrid Electric Locomotivea) The batteries
b) The ultra-capacitors
c) The diesel driven generator set
d) The global architecture
3. Energy Management Strategy
4. Conclusion and outlooks
Conclusion and outlooks
• 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
Conclusion
Outlooks
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• Aging behavior characterization of the cells thanks to long term tests
• Improvement of the optimization process thanks to the Type-2 fuzzy logic
Thanks for your attention
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