Fuzzy logic optimized threshold-based energy management strategy for fuel cell hybrid E-bike

模糊逻辑 燃料电池 计算机科学 能源管理 能量(信号处理) 汽车工程 数学优化 算法 人工智能 数学 工程类 化学工程 统计
作者
Bofei Wang,Zhen Wu,Xiongpo Hou,Yang Cheng,Tong‐Yi Guo,Huang Xiao,Jianwei Ren,Mohd Radzi Abu Mansor
出处
期刊:International Journal of Hydrogen Energy [Elsevier]
卷期号:63: 123-132 被引量:2
标识
DOI:10.1016/j.ijhydene.2024.03.100
摘要

Among the global carbon emissions in different fields, the carbon emissions in the transportation sector account for more than 1/4. Only the development of passenger car technology makes it difficult to achieve the climate goals. E-bike is considered to be one of the effective solutions. Hydrogen energy, as one of the representatives of new energy, has the advantages of cleanliness, high efficiency, and high energy density. Therefore, in this paper, a long-range hydrogen-electric hybrid bike and its energy management strategy are designed to achieve optimal performance. Herein, two energy management strategies, including the threshold-based and fuzzy logic optimized threshold-based strategy, are designed and compared by evaluating the parameters of equivalent hydrogen consumption, state of charge fluctuation, and the final state of the control system. The results show that with an initial SOC of 50% for Li-ion battery, the fuzzy logic optimized threshold-based strategy reduces equivalent hydrogen consumption by up to 16% compared to the threshold-based strategy. Besides, the fluctuation of the Li-ion battery's state of charge could be reduced by up to 54.7%, indicating that the fuzzy logic optimized threshold-based strategy is a promising energy management strategy for fuel cell hybrid E-bike.
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