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Optimal supervisory control of hybrid electric vehicles under state constraints

Abstract : Parallel hybrid electric vehicles are generally propelled by an internal combustion engine, which is combined to a reversible electric machine. The power flows between these two traction devices are determined by a supervisory control algorithm, which aims at reducing the fuel consumption and possibly some polluting emissions. In the literature, optimal control theory is now recognized as a powerful framework for the synthesis of energy management strategies for full hybrid vehicles. These strategies are referred to as “Equivalent Consumption Minimization Strategies” (ECMS) and are based on the Pontryagin Maximum Principle. To demonstrate the optimality of ECMS, it must be assumed that the storage system limits are not reached during the drive cycle. This hypothesis cannot be made anymore when considering the micro and mild hybrid vehicles studied in this thesis because the state variable generally reaches several times the boundaries. Some mathematical tools suitable for the study of state constrained optimal control problems are introduced and applied to two energy management problems. The first problem consists in determining the optimal profile of the voltage across a pack of ultra-capacitors. The second problem focuses on a dual storage system. The stress is put on the study of the optimality conditions holding in case of active state constraints. Some consequences of these conditions for the online control are pointed out are exploited for the design of a real-time controller. Its performances are assessed using a demonstrator vehicle. A comparison with a classical ECMS-based approach is also provided.
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Submitted on : Monday, September 27, 2021 - 5:42:43 PM
Last modification on : Tuesday, October 19, 2021 - 11:38:41 AM

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  • HAL Id : tel-03356195, version 1

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Clément Fontaine. Optimal supervisory control of hybrid electric vehicles under state constraints. Automatic. Université de Valenciennes et du Hainaut-Cambrésis, 2013. English. ⟨NNT : 2013VALE0024⟩. ⟨tel-03356195⟩

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