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Whole life cycle performance degradation test and RUL prediction research of fuel cell MEA

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  • Chen, Hong
  • Zhan, Zhigang
  • Jiang, Panxing
  • Sun, Yahao
  • Liao, Liwen
  • Wan, Xiongbiao
  • Du, Qing
  • Chen, Xiaosong
  • Song, Hao
  • Zhu, Ruijie
  • Shu, Zhanhong
  • Li, Shang
  • Pan, Mu

Abstract

Understanding the degradation mechanism and accurate prediction of the remaining useful life (RUL) of proton exchange membrane fuel cells (FCs) can provide guidance for improving durability and reducing their operation and maintenance costs. In this paper, we measured the actual lifetime of an FC for more than 7000 h until the end of its life and developed an RUL model based on the degradation mechanism. The particle filter (PF) algorithm was used to eliminate the influence of random errors on the key model parameters and on the prediction of RUL. RUL prediction was carried out and the contributions of key factors to FC voltage degradation were calculated and analyzed. The results demonstrated that the RUL of the FC could be accurately predicted with the RUL model and the PF algorithm. Over the lifetime of the FC, catalyst degradation was responsible for the majority of FC voltage degradation, contributing as much as 84. 3% of the performance degradation. In the latter stage of the FC lifetime, the rapid increase in leakage current caused by membrane degradation and the increase in MEA mass transfer resistance became increasingly significant, with their voltage degradation contribution rates increasing from 0.12% to 35.19% and from −4.04% to 14.32%, respectively. The influence of evolutions to the internal resistance on FC performance degradation was determined to be negligible.

Suggested Citation

  • Chen, Hong & Zhan, Zhigang & Jiang, Panxing & Sun, Yahao & Liao, Liwen & Wan, Xiongbiao & Du, Qing & Chen, Xiaosong & Song, Hao & Zhu, Ruijie & Shu, Zhanhong & Li, Shang & Pan, Mu, 2022. "Whole life cycle performance degradation test and RUL prediction research of fuel cell MEA," Applied Energy, Elsevier, vol. 310(C).
  • Handle: RePEc:eee:appene:v:310:y:2022:i:c:s0306261922000423
    DOI: 10.1016/j.apenergy.2022.118556
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    References listed on IDEAS

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    1. Chen, Huicui & Pei, Pucheng & Song, Mancun, 2015. "Lifetime prediction and the economic lifetime of Proton Exchange Membrane fuel cells," Applied Energy, Elsevier, vol. 142(C), pages 154-163.
    2. Liu, Hao & Chen, Jian & Hissel, Daniel & Su, Hongye, 2019. "Remaining useful life estimation for proton exchange membrane fuel cells using a hybrid method," Applied Energy, Elsevier, vol. 237(C), pages 910-919.
    3. Morando, S. & Jemei, S. & Hissel, D. & Gouriveau, R. & Zerhouni, N., 2017. "ANOVA method applied to proton exchange membrane fuel cell ageing forecasting using an echo state network," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 283-294.
    4. Shahgaldi, Samaneh & Alaefour, Ibrahim & Li, Xianguo, 2018. "Impact of manufacturing processes on proton exchange membrane fuel cell performance," Applied Energy, Elsevier, vol. 225(C), pages 1022-1032.
    5. Pei, Pucheng & Chen, Dongfang & Wu, Ziyao & Ren, Peng, 2019. "Nonlinear methods for evaluating and online predicting the lifetime of fuel cells," Applied Energy, Elsevier, vol. 254(C).
    6. Sutharssan, Thamo & Montalvao, Diogo & Chen, Yong Kang & Wang, Wen-Chung & Pisac, Claudia & Elemara, Hakim, 2017. "A review on prognostics and health monitoring of proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 440-450.
    7. Bressel, Mathieu & Hilairet, Mickael & Hissel, Daniel & Ould Bouamama, Belkacem, 2016. "Extended Kalman Filter for prognostic of Proton Exchange Membrane Fuel Cell," Applied Energy, Elsevier, vol. 164(C), pages 220-227.
    8. Ma, Rui & Yang, Tao & Breaz, Elena & Li, Zhongliang & Briois, Pascal & Gao, Fei, 2018. "Data-driven proton exchange membrane fuel cell degradation predication through deep learning method," Applied Energy, Elsevier, vol. 231(C), pages 102-115.
    9. Liu, Hao & Chen, Jian & Hissel, Daniel & Lu, Jianguo & Hou, Ming & Shao, Zhigang, 2020. "Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    10. Chen, Huicui & Song, Zhen & Zhao, Xin & Zhang, Tong & Pei, Pucheng & Liang, Chen, 2018. "A review of durability test protocols of the proton exchange membrane fuel cells for vehicle," Applied Energy, Elsevier, vol. 224(C), pages 289-299.
    11. Pei, Pucheng & Jia, Xiaoning & Xu, Huachi & Li, Pengcheng & Wu, Ziyao & Li, Yuehua & Ren, Peng & Chen, Dongfang & Huang, Shangwei, 2018. "The recovery mechanism of proton exchange membrane fuel cell in micro-current operation," Applied Energy, Elsevier, vol. 226(C), pages 1-9.
    12. Zhang, Tong & Wang, Peiqi & Chen, Huicui & Pei, Pucheng, 2018. "A review of automotive proton exchange membrane fuel cell degradation under start-stop operating condition," Applied Energy, Elsevier, vol. 223(C), pages 249-262.
    13. Chen, Huicui & Zhao, Xin & Qu, Bingwang & Zhang, Tong & Pei, Pucheng & Li, Congxin, 2018. "An evaluation method of gas distribution quality in dynamic process of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 232(C), pages 26-35.
    14. Chakraborty, Uttara, 2016. "Fuel crossover and internal current in proton exchange membrane fuel cell modeling," Applied Energy, Elsevier, vol. 163(C), pages 60-62.
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    5. Zhang, Zhendong & He, Hongwen & Wang, Yaxiong & Quan, Shengwei & Chen, Jinzhou & Han, Ruoyan, 2024. "A novel generalized prognostic method of proton exchange membrane fuel cell using multi-point estimation under various operating conditions," Applied Energy, Elsevier, vol. 357(C).
    6. Fan, Lixin & liu, Yang & Luo, Xiaobing & Tu, Zhengkai & Chan, Siew Hwa, 2023. "A novel gas supply configuration for hydrogen utilization improvement in a multi-stack air-cooling PEMFC system with dead-ended anode," Energy, Elsevier, vol. 282(C).
    7. Gong, Zhichao & Wang, Bowen & Xu, Yifan & Ni, Meng & Gao, Qingchen & Hou, Zhongjun & Cai, Jun & Gu, Xin & Yuan, Xinjie & Jiao, Kui, 2022. "Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle," Applied Energy, Elsevier, vol. 325(C).

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