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Automotive Engineering ›› 2025, Vol. 47 ›› Issue (7): 1296-1304.doi: 10.19562/j.chinasae.qcgc.2025.07.007

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Study on Fuel Cell Lifetime Degradation Under Real-World Driving Conditions

Wen Chang1,Genghua Shao1,Fenggang Guo1,Jinggui Zhang1,Yonghao Wu2,Hongjian Zhao1,Yin Liu1,Jian Zhang1,Dongsheng Yao1()   

  1. 1.Engineering Research Institute,Beiqi Foton Motor Co. ,Ltd. ,Beijing 102206
    2.College of Information Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617
  • Received:2025-03-07 Revised:2025-03-21 Online:2025-07-25 Published:2025-07-18
  • Contact: Dongsheng Yao E-mail:yaodongsheng@foton.com.cn

Abstract:

The coupling mechanism between life decay of proton exchange membrane fuel cells (PEMFC) and real-world driving conditions is the core bottleneck of the commercialization of hydrogen fuel vehicles (FCVS). Based on three suburban logistics fleets (60 FCVS, 2022-2024 data) in Beijing and Ningbo, in this study typical working conditions are extracted and a voltage attenuation model is constructed. The results show that: (1) the attenuation is accelerated under high frequency conditions (high frequency, long distance transport), which corresponds to the dissolution mechanism of the catalytic layer and the aging mechanism of the diffusion layer; (2) In typical suburban working conditions, the deterioration of urban working conditions is significant, which verifies that frequent start-stop accelerates platinum agglomeration and membrane damage; (3) The attenuation rate of southern coastal suburban conditions (Ningbo: high temperature and humidity, salt spray environment) is 5 times that of similar conditions in Beijing, mainly due to electrochemical corrosion of PEMFC plate; (4) High data-driven linear model fitting degree (>98%), verifies the feasibility of life prediction. This study provides quantitative support for durability design and regional operation of PEMFC.

Key words: real-world driving conditions, fuel cell vehicle (FCV), proton exchange membrane fuel cell (PEMFC), performance degradation prediction