IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v381y2025ics0306261924025741.html
   My bibliography  Save this article

Fuel cell current degradation law and I-V performance prediction

Author

Listed:
  • Pei, Pucheng
  • Fan, Tengbo
  • Ren, Peng
  • Wang, Mingkai
  • Chen, Dongfang
  • Meng, Yining
  • Tan, Mingbo
  • Shen, Hailin
  • Zhou, Wenping

Abstract

The lifespan assessment of fuel cells is often too time-consuming for widespread implementation. Consequently, a reliable method for predicting their lifetime is essential to accurately evaluate their durability. Studying the ageing laws of fuel cells is crucial for lifetime prediction. In this study, the current degradation law is formulated based on the durability test results of 85 fuel cell samples. It demonstrates that the logarithm of fuel cell current decreases linearly over time under constant voltage conditions, and that the decay of the I-V curve follows the transverse compression law during the ageing process. This behavior is then explained as the degradation of the roughness factor (RF) and the dependence of the water and heat state on operating voltage. The causes of deviations from the decay law in certain cases are analysed. It's recommended to avoid the accumulation of water and nitrogen within the internal flow field of fuel cell during testing. Furthermore, a method for constructing the I-V curve is proposed, allowing the prediction of the I-V curve at any time during the stable decay period using the measured results of an I-V curve at a certain time and a working point at another. The determination coefficient for predicted I-V curves in two fuel cell cases exceeds 0.98. Lastly, an online lifetime prediction method is developed, enabling real-time estimation of both the remaining lifetime and the service lifetime based on a lifetime determination criterion during operation.

Suggested Citation

  • Pei, Pucheng & Fan, Tengbo & Ren, Peng & Wang, Mingkai & Chen, Dongfang & Meng, Yining & Tan, Mingbo & Shen, Hailin & Zhou, Wenping, 2025. "Fuel cell current degradation law and I-V performance prediction," Applied Energy, Elsevier, vol. 381(C).
  • Handle: RePEc:eee:appene:v:381:y:2025:i:c:s0306261924025741
    DOI: 10.1016/j.apenergy.2024.125190
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924025741
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2024.125190?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wu, Ziyao & Pei, Pucheng & Xu, Huachi & Jia, Xiaoning & Ren, Peng & Wang, Bozheng, 2019. "Study on the effect of membrane electrode assembly parameters on polymer electrolyte membrane fuel cell performance by galvanostatic charging method," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Ren, Peng & Pei, Pucheng & Chen, Dongfang & Li, Yuehua & Wu, Ziyao & Zhang, Lu & Li, Zizhao & Wang, Mingkai & Wang, He & Wang, Bozheng & Wang, Xizhong, 2022. "Novel analytic method of membrane electrode assembly parameters for fuel cell consistency evaluation by micro-current excitation," Applied Energy, Elsevier, vol. 306(PB).
    3. 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.
    4. 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.
    5. Chen, Dongfang & Pei, Pucheng & Meng, Yining & Ren, Peng & Li, Yuehua & Wang, Mingkai & Wang, Xizhong, 2022. "Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells," Energy, Elsevier, vol. 255(C).
    6. Zhu, Wenchao & Li, Changzhi & Xu, Yafei & Yang, Wenlong & Xie, Changjun, 2024. "High accuracy and adaptability of PEMFC degradation interval prediction with Informer-GPR under dynamic conditions," Energy, Elsevier, vol. 307(C).
    7. Kurnia, Jundika C. & Sasmito, Agus P. & Shamim, Tariq, 2019. "Advances in proton exchange membrane fuel cell with dead-end anode operation: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Pei, Pucheng & Wu, Ziyao & Li, Yuehua & Jia, Xiaoning & Chen, Dongfang & Huang, Shangwei, 2018. "Improved methods to measure hydrogen crossover current in proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 215(C), pages 338-347.
    9. Zhou, Daming & Gao, Fei & Breaz, Elena & Ravey, Alexandre & Miraoui, Abdellatif, 2017. "Degradation prediction of PEM fuel cell using a moving window based hybrid prognostic approach," Energy, Elsevier, vol. 138(C), pages 1175-1186.
    10. Yang, Jibin & Wang, Le & Zhang, Bo & Zhang, Han & Wu, Xiaohua & Xu, Xiaohui & Deng, Pengyi & Peng, Yiqiang, 2024. "Remaining useful life prediction of vehicle-oriented PEMFC systems based on IGWO-BP neural network under real-world traffic conditions," Energy, Elsevier, vol. 291(C).
    11. 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.
    12. 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.
    13. 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).
    14. Pei, Pucheng & Meng, Yining & Chen, Dongfang & Ren, Peng & Wang, Mingkai & Wang, Xizhong, 2023. "Lifetime prediction method of proton exchange membrane fuel cells based on current degradation law," Energy, Elsevier, vol. 265(C).
    15. Rabbani, Abid & Rokni, Masoud, 2013. "Effect of nitrogen crossover on purging strategy in PEM fuel cell systems," Applied Energy, Elsevier, vol. 111(C), pages 1061-1070.
    16. Ren, Lei & Zhou, Sheng & Ou, Xunmin, 2020. "Life-cycle energy consumption and greenhouse-gas emissions of hydrogen supply chains for fuel-cell vehicles in China," Energy, Elsevier, vol. 209(C).
    17. 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).
    18. 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.
    19. Tian, Lei & Gao, Yan & Yang, Haiyu & Wang, Renkang, 2025. "Multi-scenario long-term degradation prediction of PEMFC based on generative inference informer model," Applied Energy, Elsevier, vol. 377(PA).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pei, Pucheng & Meng, Yining & Chen, Dongfang & Ren, Peng & Wang, Mingkai & Wang, Xizhong, 2023. "Lifetime prediction method of proton exchange membrane fuel cells based on current degradation law," Energy, Elsevier, vol. 265(C).
    2. 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).
    3. 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).
    4. Chen, Dongfang & Pei, Pucheng & Ren, Peng & Song, Xin & Wang, He & Zhang, Lu & Wang, Mingkai, 2022. "Analytical methods for the effect of anode nitrogen concentration on performance and voltage consistency of proton exchange membrane fuel cell stack," Energy, Elsevier, vol. 258(C).
    5. Song, Ke & Huang, Xing & Huang, Pengyu & Sun, Hui & Chen, Yuhui & Huang, Dongya, 2024. "Data-driven health state estimation and remaining useful life prediction of fuel cells," Renewable Energy, Elsevier, vol. 227(C).
    6. Chen, Dongfang & Pei, Pucheng & Meng, Yining & Ren, Peng & Li, Yuehua & Wang, Mingkai & Wang, Xizhong, 2022. "Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells," Energy, Elsevier, vol. 255(C).
    7. Ren, Peng & Meng, Yining & Pei, Pucheng & Fu, Xi & Chen, Dongfang & Li, Yuehua & Zhu, Zijing & Zhang, Lu & Wang, Mingkai, 2023. "Rapid synchronous state-of-health diagnosis of membrane electrode assemblies in fuel cell stacks," Applied Energy, Elsevier, vol. 330(PA).
    8. Ke Song & Yimin Wang & Xiao Hu & Jing Cao, 2020. "Online Prediction of Vehicular Fuel Cell Residual Lifetime Based on Adaptive Extended Kalman Filter," Energies, MDPI, vol. 13(23), pages 1-21, November.
    9. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Ren, Peng & Pei, Pucheng & Chen, Dongfang & Li, Yuehua & Wu, Ziyao & Zhang, Lu & Li, Zizhao & Wang, Mingkai & Wang, He & Wang, Bozheng & Wang, Xizhong, 2022. "Novel analytic method of membrane electrode assembly parameters for fuel cell consistency evaluation by micro-current excitation," Applied Energy, Elsevier, vol. 306(PB).
    11. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    12. 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).
    13. Chen, Dongfang & Wu, Wenlong & Chang, Kuanyu & Li, Yuehua & Pei, Pucheng & Xu, Xiaoming, 2023. "Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization," Energy, Elsevier, vol. 285(C).
    14. Chen, Kui & Badji, Abderrezak & Laghrouche, Salah & Djerdir, Abdesslem, 2022. "Polymer electrolyte membrane fuel cells degradation prediction using multi-kernel relevance vector regression and whale optimization algorithm," Applied Energy, Elsevier, vol. 318(C).
    15. Pan, Mingzhang & Pan, Chengjie & Li, Chao & Zhao, Jian, 2021. "A review of membranes in proton exchange membrane fuel cells: Transport phenomena, performance and durability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    16. Krystof Foniok & Lubomira Drozdova & Lukas Prokop & Filip Krupa & Pavel Kedron & Vojtech Blazek, 2025. "Mechanisms and Modelling of Effects on the Degradation Processes of a Proton Exchange Membrane (PEM) Fuel Cell: A Comprehensive Review," Energies, MDPI, vol. 18(8), pages 1-64, April.
    17. Ren, Peng & Pei, Pucheng & Chen, Dongfang & Zhang, Lu & Li, Yuehua & Song, Xin & Wang, Mingkai & Wang, He, 2022. "Corrosion of metallic bipolar plates accelerated by operating conditions in a simulated PEM fuel cell cathode environment," Renewable Energy, Elsevier, vol. 194(C), pages 1277-1287.
    18. Zuo, Jian & Lv, Hong & Zhou, Daming & Xue, Qiong & Jin, Liming & Zhou, Wei & Yang, Daijun & Zhang, Cunman, 2021. "Deep learning based prognostic framework towards proton exchange membrane fuel cell for automotive application," Applied Energy, Elsevier, vol. 281(C).
    19. 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).
    20. Liu, Ze & Xu, Sichuan & Zhao, Honghui & Wang, Yupeng, 2022. "Durability estimation and short-term voltage degradation forecasting of vehicle PEMFC system: Development and evaluation of machine learning models," Applied Energy, Elsevier, vol. 326(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:381:y:2025:i:c:s0306261924025741. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.