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首页> 外文期刊>International Journal of Automotive Technology >Energy Management Strategy of Fuel Cell/Battery Hybrid Vehicle Based on Series Fuzzy Control
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Energy Management Strategy of Fuel Cell/Battery Hybrid Vehicle Based on Series Fuzzy Control

机译:基于串联模糊控制的燃料电池/电池混合动力汽车能量管理策略

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摘要

Fuel cell durability and vehicle operating cost are the main optimization goals of energy management strategy (EMS) for fuel cell hybrid electric vehicles (FCHEV). In this paper, a series fuzzy control strategy (SFCS) is proposed to decrease the load changing rate of fuel cell system (FCs). The test bench is used to obtain the output characteristics and load changing capacity of FCs. In order to increase the driving mileage and to eliminate the uncertainty of manual experience in fuzzy controller, particle swarm optimization (PSO) is used to optimize the subjection function distribution and rule weights of fuzzy control, and the evaluation function is constructed by operating cost. Based on the experiment data of FC and battery, the model of the vehicle and strategy are constructed in the software environment, and the optimization result is obtained through simulation. The results show that the FCs load changing rate is reduced and limited to the range of change capacity through the SFCS, while the durability of the fuel cell is optimized. The SFCS optimized by PSO (PSFCS) increases the driving mileage. Under WLTC and UDDS conditions, mileage has been increased by 11.2 % and 8.79 % respectively.
机译:燃料电池耐久性和车辆运行成本是燃料电池混合动力汽车(FCHEV)能量管理策略(EMS)的主要优化目标。该文提出一种串联模糊控制策略(SFCS)来降低燃料电池系统(FCs)的负荷变化率。该试验台用于获取FC的输出特性和负载转换能力。为了增加行驶里程,消除模糊控制器人工体验的不确定性,采用粒子群优化(PSO)对模糊控制的主体函数分布和规则权重进行优化,并利用运营成本构建评价函数。基于FC和电池的实验数据,在软件环境中构建了车辆模型和策略,并通过仿真得到优化结果。结果表明,通过SFCS降低了燃料电池的负荷变化率,并将其限制在变化能力范围内,同时优化了燃料电池的耐久性。通过PSO(PSFCS)优化的SFCS增加了行驶里程。在WLTC和UDDS条件下,行驶里程分别增加了11.2%和8.79%。

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