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On-line energy management for HEV based on particle swarm optimization

Published online by Cambridge University Press:  19 May 2011

S. Caux ,
D. Wanderley-Honda ,
D. Hissel  and
M. Fadel
S. Caux*
Affiliation:
LAboratoire PLAsma et Conversion d'Énergie, LAPLACE UMR 5213 CNRS, INPT, UPS, 2 rue Camichel, 31071 Toulouse, France
D. Wanderley-Honda
Affiliation:
LAboratoire PLAsma et Conversion d'Énergie, LAPLACE UMR 5213 CNRS, INPT, UPS, 2 rue Camichel, 31071 Toulouse, France
D. Hissel
Affiliation:
FEMTO-St, FCLAB, Université de Franche-Comté, UMR 6174, 90010 Belfort, France
M. Fadel
Affiliation:
LAboratoire PLAsma et Conversion d'Énergie, LAPLACE UMR 5213 CNRS, INPT, UPS, 2 rue Camichel, 31071 Toulouse, France
*
aemail: stephane.caux@laplace.enseeiht.fr
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Abstract

This study considers a Hybrid Electrical Vehicle supplied by a Fuel Cell stack and supercapacitors used as Storage Element. In such an application, real time energy management is of paramount importance in order to increase autonomy and be able to deal on-line with perturbed power demand. Many offline power flow optimization principles are available but online algorithms are preferred and should be derived for optimal management of the instantaneous power splitting between the different available power sources. Based on particle swarm optimization algorithm, this study defines the parameters tuning of such algorithm. The final power splitting allows not only recovering energy braking but also is robust to some disturbances occurring during the trip. The solution provides good-quality and high-robustness results in a certain class of mission profile and power disturbance.

Type
Research Article
Information
The European Physical Journal - Applied Physics , Volume 54 , Issue 2: Focus on Fuel Cells 2009 , May 2011 , 23403
Copyright
© EDP Sciences, 2011

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