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Proton exchange membrane fuel cell system prognostics and decision-making: Current status and perspectives

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  • Yue, Meiling
  • Jemei, Samir
  • Zerhouni, Noureddine
  • Gouriveau, Rafael

Abstract

Proton exchange membrane fuel cell (PEMFC), as an attractive alternative power source, has seen its increasing deployment in both automotive and small stationary applications. To improve the durability of the PEMFC system, recent research has engaged in developing prognostics and health management methods. Although the prognostics methods have been extensively studied to improve the prediction accuracy, some critical issues have not been fully addressed. For example, few studies have looked into the prognostics methods by different criteria and under dynamic operation conditions, and none of them have investigated the data availability and quality for PEMFC prognostics. Due to the lack of more comprehensive and general prognostics methods as well as the limitations in data, studies in the post-prognostics decision-making phase have hardly ever been initiated. This paper tends to provide a full review of the existing prognostics research by analysing the prognostics scales, horizon, threshold, and the use of methods. The data used in the previous studies has also been investigated. Moreover, four principal directions of post-prognostics decision-making have been proposed and discussed. According to the findings, research challenges and development perspectives in the aspects of data, prognostics and decision-making are proposed.

Suggested Citation

  • Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine & Gouriveau, Rafael, 2021. "Proton exchange membrane fuel cell system prognostics and decision-making: Current status and perspectives," Renewable Energy, Elsevier, vol. 179(C), pages 2277-2294.
  • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:2277-2294
    DOI: 10.1016/j.renene.2021.08.045
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    References listed on IDEAS

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    Cited by:

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    4. Aihua Tang & Yuanhang Yang & Quanqing Yu & Zhigang Zhang & Lin Yang, 2022. "A Review of Life Prediction Methods for PEMFCs in Electric Vehicles," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    5. Zhang, Xin & Rahman, Ehsanur, 2022. "Thermodynamic analysis and optimization of a hybrid power system using thermoradiative device to efficiently recover waste heat from alkaline fuel cell," Renewable Energy, Elsevier, vol. 200(C), pages 1240-1250.
    6. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    7. 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).

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