Identification and monitoring of a PEM electrolyser based on dynamical modelling

Abstract

To improve the efficiency and the safety of hydrogen electrolysis stations, some technological studies are still under investigation both on methods and materials. As methods, control, monitoring and diagnosis algorithms are relevant tools. This work focuses on the dynamical modelling and the monitoring of Proton Exchange Membrane (PEM) electrolyser. Our contribution consists of three parts: to propose a model of an analytical–dynamical PEM electrolyser, dedicated to control and monitoring; to identify the model parameters and to propose adequate monitoring tools. The proposed model is deduced from physical laws and electrochemical equations and consists of a steady-state electric model coupled with a dynamic thermal model. The estimation of the model parameters is achieved using identification and data fitting techniques based on experimental measurements. Taking into account the information given by the proposed analytical model and the experimentation data (temperature T, voltage U and current I) given by a PEM electrolyser, the model parameters are identified. After estimating the dynamical model, model-based diagnosis is used to monitor the PEM electrolyser and to ensure its safety. We illustrate how our algorithm can detect and isolate faults on actuators, on sensors or on electrolyser system.