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Communication Dans Un Congrès Année : 2010

Predictive energy management for hybrid electric vehicles - Prediction horizon and battery capacity sensitivity

Maxime Debert
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Guillaume Colin
Yann Chamaillard
Benoit Bellicaud
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Résumé

Increasing information about future driving conditions in vehicles makes predictive energy management realistic. This energy management strategy uses a dynamic programming algorithm on a sliding window in order to minimize the hybrid vehicle fuel consumption. For real time implementation, it is necessary to reduce computational time so as to embed this control on an automotive calculator. This paper focuses on the in uence of the prediction horizon and battery capacity on CO2 emission in the case of a combined hybrid electric vehicle.
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Dates et versions

hal-00616604 , version 1 (23-08-2011)

Identifiants

  • HAL Id : hal-00616604 , version 1

Citer

Maxime Debert, Guillaume Colin, Yann Chamaillard, Lino Guzzella, Ahmed Ketfi-Cherif, et al.. Predictive energy management for hybrid electric vehicles - Prediction horizon and battery capacity sensitivity. IFAC Symposium Advances in Automotive Control, Jul 2010, Munich, Germany. pp.AAC 2010. ⟨hal-00616604⟩
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