Research on Energy Management Strategies for Fuel Cell Hybrid Vehicles Based on Time Classification

Lihua Ye, Zixing Zhang, Qinglong Zhao, Xu Zhao, Zhou He and Aiping Shi ()
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Lihua Ye: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Zixing Zhang: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Qinglong Zhao: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Xu Zhao: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Zhou He: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Aiping Shi: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China

Energies, 2025, vol. 18, issue 8, 1-29

Abstract: In order to minimize the carbon emission and energy consumption of fuel cell hybrid vehicles and, at the same time, solve the problem of low accuracy of working condition identification in the working condition identification strategy, this paper proposes an energy management strategy for SUVs on the basis of the working condition identification energy management strategy by using the time classification method. First, the mathematical model of the whole vehicle power system is established, and the driving conditions are constructed using actual collected vehicle driving data. On this basis, the working condition identification model was established, and then the energy management strategy of time working condition classification was established on the basis of the working condition identification model, and the equivalent hydrogen consumption of the two strategies was calculated by the Pontryagin minimization strategy. The results show that the strategy proposed in this paper reduces the equivalent hydrogen consumption by 2.707% compared with the condition identification strategy. This improvement not only greatly improves the energy efficiency of the fuel cell hybrid vehicle but also provides new ideas for the optimization of future energy management strategies.

Keywords: fuel cell; condition recognition; time classification; equivalent hydrogen consumption; time classification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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