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Communication Dans Un Congrès Année : 2010

A real time neural energy management strategy for a hybrid pneumatic engine

Guillaume Colin
Gérard Bloch
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Yann Chamaillard
Andrej Ivanco
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Résumé

Various energy management strategies for a hybrid pneumatic engine are reviewed and a real time neural control strategy proposed. This Neural Network strategy learns off line the optimal control given by Dynamic Programming and the resulting control model is applied on line. The dierent strategies are simulated with a backward vehicle model for various driving cycles and their fuel consumptions compared. The results show that the Neural Network strategy is better than a classical Equivalent Consumption Minimization Strategy (ECMS) and equivalent to a Variable Penalty Coecient Strategy with Driving Pattern Recognition.
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Dates et versions

hal-00476666 , version 1 (26-04-2010)

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  • HAL Id : hal-00476666 , version 1

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Guillaume Colin, Gérard Bloch, Yann Chamaillard, Andrej Ivanco. A real time neural energy management strategy for a hybrid pneumatic engine. IFAC Symposium Advances in Automotive Control, AAC 2010, Jul 2010, Munich, Germany. pp.CDROM. ⟨hal-00476666⟩
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