When analysing the integration of electrolysers with renewable energy systems, it is common to obtain hydrogen generation from mathematical models. Many models currently used for techno-economic analysis do not consider system degradation, which leads to an overestimation of generated hydrogen. When analysing economic feasibility of electrolyser use it is essential to account for such degradation, which leads to progressive decline in hydrogen generation and leads to higher operational expenditure (OPEX).

To develop appropriate degradation models, it is necessary to properly monitor electrolyser operation, understanding specific degradation pathways and patterns. Monitoring the voltage evolution allows to get a general understanding of the evolution of the system. However, through the use of in-operando Electrochemical Impedance Spectroscopy (EIS) it is possible to monitor degradation of different processes in the electrolyser, which can then be linked to specific components. Understanding how each component degrades under different operational profiles aids in the development of accurate models that can be used to adapt operational schemes to reduce degradation and therefore OPEX.

Processing of EIS data is not trivial, and it is necessary to develop a framework that will allow for the automatic processing of signals and obtention of meaningful KPIs to monitor the system’s state and inform decision making. 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 inside the electrolyser. Through signal analysis, processes are identified and the resistance associated with each is extracted. The evolution of the resistances is then analyzed to evaluate how total degradation is affected by each.

This condition monitoring scheme has been tested for a lab-scale single PEM cell at a laboratory in our facilities and is easily scalable to larger systems. Through this analysis it has been possible to separate the evolution of the resistances of mass transport, charge transfer and ionic transfer and understand how each one contributes to total degradation.