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.

In this study, we evaluated the effectiveness of various frequency response analysis (FRA) techniques for identifying fault states in the diagnosis of polymer electrolyte membrane fuel cells (PEMFCs). To this end, an identifiability analysis was conducted to determine the reliability of parameters obtained by fitting a previously validated PEMFC model to the spectra from different methods. Specifically, we focused on electrochemical impedance spectroscopy (EIS) and the newly introduced concentration frequency response analysis (CFRA). The identifiability analysis revealed that CFRA, when applied with water pressure as the input and voltage as the output, provides the most accurate parameters estimates related to mass transport in the cathode electrode and the Nafion electrolyte, yielding physically meaningful insights. Consequently, employing this input for PEMFC diagnosis emerges as a promising approach. Furthermore, our findings underscore the importance of meticulously evaluating the quality of parameter estimation, even when utilizing well-established techniques such as EIS.