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access icon free Energy management strategy for a fuel cell hybrid vehicle based on maximum efficiency and maximum power identification

© The Institution of Engineering and Technology
Received 03/01/2016, Accepted 25/07/2016, Revised 06/05/2016, Published 27/07/2016

This paper addresses the energy management strategy (EMS) for a fuel cell hybrid electric vehicle (FC-HEV). The fuel cell system (FCS) is a multi-physics system, and consequently, its energetic performances depend on the degradation and on the operating conditions. The maximum power (MP) and the maximum efficiency (ME) points of the FCS are unique but they move with operating condition variations. Thus, developing an extremum seeking process (ESP) for both MP and ME tracking is a challenging task. In the ESP, models are identified online by using an adaptive recursive least square (ARLS) method to seek a variation in the FCS performances. Then an optimisation algorithm is used on the updated model to find the MP and the ME points. The ESP is incorporated into a hysteresis power splitting control (HPSC). A MP mode or a ME mode can be set based on the energy storage level (battery pack). The effectiveness of the proposed MP- and ME-ESP EMS is demonstrated by conducting experimental studies on two FCSs with different levels of degradation. It was demonstrated that the classical EMS based on maps are not valid when the operating parameters vary because of the level of degradation change.

Inspec keywords: optimisation; adaptive estimation; recursive estimation; least squares approximations; fuel cell vehicles; hybrid electric vehicles; energy management systems

Other keywords: fuel cell system; hysteresis power splitting control; multiphysics system; FC-HEV; extremum seeking process; maximum efficiency point; energy management strategy; adaptive recursive least square method; ESP; energy storage level; fuel cell hybrid electric vehicle; maximum power identification; HPSC; FCS; optimisation algorithm; MP tracking; ME tracking

Subjects: Other topics in statistics; Fuel cells; Optimisation techniques; Interpolation and function approximation (numerical analysis); Transportation

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