Neural Network Based Model for a PEM Fuel Cell System

Abstract

Usually, modelling of fuel cell systems uses complex expressions, based on the knowledge of physical chemical phenomena. These models require a good knowledge of the parameters involved in the processes that, in many cases, are difficult to determine. A solution to avoid this difficulty consists in using black-box models, such as those based on artificial neural networks (ANN). This paper presents the modelling of a PEM fuel cell system, using ANNs. The selected ANN structure has been validated for the transient state, during the start up of the system, and in steady state. Results are shown for a commercial PEM fuel cell system.