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Polymer Electrolyte Fuel Cell Degradation Mechanisms and Their Diagnosis by Frequency Response Analysis Methods: A Review

Author

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  • Antonio Sorrentino

    (Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, D-39106 Magdeburg, Germany)

  • Kai Sundmacher

    (Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, D-39106 Magdeburg, Germany
    Process Systems Engineering, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, D-39106 Magdeburg, Germany)

  • Tanja Vidakovic-Koch

    (Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, D-39106 Magdeburg, Germany)

Abstract

Several experimental techniques involving dynamic electrical variables are used to study the complex behaviour of polymer electrolyte membrane fuel cells in order to improve performance and durability. Among them, electrochemical impedance spectroscopy (EIS) is one of the most employed methods. Like any frequency response analysis (FRA) methodology, EIS enables one to separate the contribution of many processes to performance losses. However, it fails to identify processes with a similar time constant and the interpretation of EIS spectra is often ambiguous. In the last decade, alternative FRA methodologies based on non-electrical inputs and/or outputs have been developed. These studies were mainly driven by requirements for a better diagnosis of polymer electrolyte membrane fuel cells (PEMFCs) faulty operation conditions as well as better component and material design. In this contribution, a state-of-the-art EIS and novel FRA techniques for PEMFC diagnosis are summarised. First, common degradation mechanisms and their causes are discussed. A mathematical framework based on linear system theory of time invariant systems is described in order to explain the theoretical implications of the use of different input/output configurations. In relation to this, the concepts and potential are depicted as well as the problematic aspects and future prospective of these diagnostic approaches.

Suggested Citation

  • Antonio Sorrentino & Kai Sundmacher & Tanja Vidakovic-Koch, 2020. "Polymer Electrolyte Fuel Cell Degradation Mechanisms and Their Diagnosis by Frequency Response Analysis Methods: A Review," Energies, MDPI, vol. 13(21), pages 1-28, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:21:p:5825-:d:441596
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    References listed on IDEAS

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    1. Baricci, Andrea & Mereu, Riccardo & Messaggi, Mirko & Zago, Matteo & Inzoli, Fabio & Casalegno, Andrea, 2017. "Application of computational fluid dynamics to the analysis of geometrical features in PEM fuel cells flow fields with the aid of impedance spectroscopy," Applied Energy, Elsevier, vol. 205(C), pages 670-682.
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    Cited by:

    1. Zhang, Caizhi & Zhang, Yuqi & Wang, Lei & Deng, Xiaozhi & Liu, Yang & Zhang, Jiujun, 2023. "A health management review of proton exchange membrane fuel cell for electric vehicles: Failure mechanisms, diagnosis techniques and mitigation measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Rocha, A. & Ferreira, R.B. & Falcão, D.S. & Pinto, A.M.F.R., 2023. "Experimental study on a unitized regenerative fuel cell operated in constant electrode mode: Effect of cell design and operating conditions," Renewable Energy, Elsevier, vol. 215(C).
    3. Ewa Janicka & Michal Mielniczek & Lukasz Gawel & Kazimierz Darowicki, 2021. "Optimization of the Relative Humidity of Reactant Gases in Hydrogen Fuel Cells Using Dynamic Impedance Measurements," Energies, MDPI, vol. 14(11), pages 1-11, May.
    4. Huu Linh Nguyen & Jeasu Han & Xuan Linh Nguyen & Sangseok Yu & Young-Mo Goo & Duc Dung Le, 2021. "Review of the Durability of Polymer Electrolyte Membrane Fuel Cell in Long-Term Operation: Main Influencing Parameters and Testing Protocols," Energies, MDPI, vol. 14(13), pages 1-34, July.
    5. Alexey Loskutov & Andrey Kurkin & Andrey Shalukho & Ivan Lipuzhin, 2022. "New Trends and Prospects for Developing Local Power Sources Based on Fuel Cells and Power Storage Units for Critical Infrastructure Customers," Energies, MDPI, vol. 16(1), pages 1-16, December.
    6. Martín Antonio Rodríguez Licea & Francisco Javier Pérez Pinal & Allan Giovanni Soriano Sánchez, 2021. "An Overview on Electric-Stress Degradation Empirical Models for Electrochemical Devices in Smart Grids," Energies, MDPI, vol. 14(8), pages 1-23, April.

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