A GM-Based Energy Management Strategy of Hybrid Power System for Hydrogen Fuel Cell Buses

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作者
Wang, Yuan [1 ]
Lu, Jianshan [1 ]
Zhu, Xinyu [1 ]
Ye, Jianfeng [1 ]
Kong, You [2 ]
Hao, Weina [1 ]
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[1] College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou,310023, China
[2] College of Transport and Communication, Shanghai Maritime University, Shanghai,201303, China
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Hydrogen energy is a clean, carbon-free, flexible, efficient, and widely used secondary energy source, which is an ideal alternative to promote the clean and efficient use of traditional fossil fuels. Hydrogen fuel cell bus has the advantages of a high-energy conversion rate, absolute pollution-free, sufficient raw materials, and convenient filling. The hybrid power system, composed of fuel cell and auxiliary energy source, is one of the key technologies to promote the development of hydrogen fuel cell vehicle. This study aims to propose an energy management strategy by analyzing the output characteristics and power allocation of fuel cell and power battery in the hybrid power mode with fuel cell as the main and battery as the auxiliary. A GM (1, N) power prediction strategy was proposed and compared with other strategies as an on-off control strategy and logical threshold value strategy in this study. The variation curves of the battery SOC and fuel cell output power under two working conditions of CCBC and real vehicle conditions were analyzed by using these three strategies, when the initial SOC of power battery is 30%, 70%, and 90%, respectively. Results showed that the power prediction strategy based on GM (1, N) has a better performance in output efficiency and fuel economy when compared to the other two strategies by analyzing the aspects of the battery in the SOC variation and equivalent hydrogen consumption and the fuel cell in the output power variation and hydrogen consumption. This research can be helpful to provide the suggested solution for energy management of the hybrid power system for hydrogen fuel cell buses. © 2023 Yuan Wang et al.
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