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

Stéphane Caux (1) , Daniel Wanderley-Honda (2) , Daniel Hissel (3) , Maurice Fadel (1)

1 LAPLACE-CODIASE - COmmande et DIAgnostic des Systèmes Electriques
2 LAPLACE - LAboratoire PLasma et Conversion d'Energie
3 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

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.

Mots clés: Physical Sciences; Particle Swarm Optimization; Hybrid Electric Vehicle; Multi-source System

Domaines: Physique [physics]

Stéphane Caux, Daniel Wanderley-Honda, Daniel Hissel, Maurice Fadel. On-line energy management for HEV based on particle swarm optimization. 2010 IEEE Vehicle Power and Propulsion Conference, Sep 2010, Lille, France. ⟨10.1051/epjap/2010100248⟩. ⟨hal-00699043⟩