When analysing the integration of electrolysers with renewable energy systems, it is common to obtain hydrogen generation from mathematical models, many of which do not consider system degradation, leading to an overestimation of hydrogen generation.

To develop appropriate models, it is necessary to monitor electrolyser operation and understand specific degradation pathways. Monitoring the voltage evolution provides a general understanding of the system. However, through the use of in-operando electrochemical impedance spectroscopy (EIS) it is possible to monitor degradation of different processes, which can be linked to specific electrolyser components.

Processing EIS data is not trivial, and it is necessary to develop a framework that will allow for its automatic analysis and monitoring of the system’s state. In this paper, we propose a framework based on EIS data and the distribution of relaxation times (DRT) to automatically extract data corresponding to various processes. Through signal analysis, processes are identified and their resistances are extracted.

This condition monitoring scheme is tested for a lab-scale single PEM cell at Tekniker's laboratory, being easily scalable to larger systems. This enables the separation of mass, charge, and ionic transport processes and helps to understand their evolution and how each one contributes to total degradation.