首页> 外文期刊>International journal of hydrogen energy >Optimization based energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle considering fuel economy and fuel cell lifespan
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Optimization based energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle considering fuel economy and fuel cell lifespan

机译:考虑燃料经济性和燃料电池寿命的基于优化的燃料电池/电池/超级电容器混合动力汽车能源管理策略

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Optimization of energy management strategy (EMS) for fuel cell/battery/ultracapacitor hybrid electrical vehicle (FCHEV) is primarily aimed on reducing fuel consumption. However, serious power fluctuation has effect on the durability of fuel cell, which still remains one challenging barrier for FCHEVs. In this paper, we propose an optimized frequency decoupling EMS using fuzzy control method to extend fuel cell lifespan and improve fuel economy for FCHEV. In the proposed EMS, fuel cell, battery and ultracapacitor are employed to supply low, middle and high-frequency components of required power, respectively. For accurately adjusting membership functions of proposed fuzzy controllers, genetic algorithm (GA) is adopted to optimize them considering multiple constraints on fuel cell power fluctuation and hydrogen consumption. The proposed EMS is verified by Advisor-Simulink and experiment bench. Simulation and experimental results confirm that the proposed EMS can effectively reduce hydrogen consumption in three typical drive cycles, limit fuel cell power fluctuation within 300 W/s and thus extend fuel cell lifespan. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:燃料电池/电池/超级电容器混合动力汽车(FCHEV)的能源管理策略(EMS)的优化主要旨在减少燃料消耗。但是,严重的功率波动会影响燃料电池的耐用性,这仍然是FCHEV的一大挑战。在本文中,我们提出了一种采用模糊控制方法的优化频率解耦EMS,以延长FCHEV的燃料电池寿命并提高燃料经济性。在建议的EMS中,燃料电池,电池和超级电容器分别用于提供所需功率的低频,中频和高频分量。为了精确地调整所提出的模糊控制器的隶属函数,考虑了对燃料电池功率波动和氢消耗的多重约束,采用遗传算法(GA)对其进行优化。建议的EMS已通过Advisor-Simulink和实验台进行了验证。仿真和实验结果证实,提出的EMS可以有效地减少三个典型驾驶循环中的氢消耗,将燃料电池的功率波动限制在300 W / s以内,从而延长燃料电池的使用寿命。 (C)2020 Hydrogen Energy Publications LLC。由Elsevier Ltd.出版。保留所有权利。

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