Proton exchange membrane fuel cells play a vital role in achieving a hydrogen-powered, carbon-neutral society. Although they have been deployed in stationary and transportation applications, their limited durability and reliability still restrict large-scale commercialization. Assessing internal health states is critical to overcoming these challenges by preventing operational faults and minimizing degradation rates. However, hydrogen fuel cells are highly nonlinear, multiscale, and multiphysics systems, hindering the estimation of system health states. This review investigates a nondestructive and in situ characterization technique, electrochemical impedance spectroscopy (EIS), to characterize the health states of hydrogen fuel cells. The variation in internal health states is directly reflected in the impedance spectrum, which can be assessed through proper interpretation. Nevertheless, developing EIS for hydrogen fuel cells is a nontrivial task. Implementing and applying EIS requires interdisciplinary studies in signal processing, control theory, and machine learning in particular cases. This review systematically discusses the implementation, interpretation, and application of EIS for hydrogen fuel cells. The onboard applicability and short measurement time are key factors in EIS implementation. Model-based and DRT-based interpretation approaches are reviewed for efficiently extracting valuable health states. Based on these methods, the applications of EIS in performance characterization, fault diagnosis, degradation analysis, and prognostics are discussed. Four perspectives regarding general, non-electrical, localized, and multiphysics-integrated EIS, are proposed to highlight and guide EIS-related studies in hydrogen fuel cells. This review provides a comprehensive overview of the deployment and application of EIS in hydrogen fuel cells and offers insights into addressing durability and reliability challenges.
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Zuo et al. (2026) studied this question.
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