PEM Fuel Cell Modelling Using Artificial Neural Networks (ANN)

Fuel cells (FC) convert directly into a dc electrical energy the chemical energy of a reaction of hydrogen and oxygen. Proton Exchange Membrane (PEMFC) is a suitable alternative for both electrical transportation and stationary applications. This article deals with an Artificial Neural Network (ANN) modelling method of a PEMFC. This modelling approach permits to describe both transient and steady state behaviours of the PEMFC voltage. Furthermore, the prediction of the operating temperature of a PEMFC based only on its measured voltage and current is proposed and tested successfully. Indeed, experimental data from a 1.2 kW Nexa Ballard PEMFC is used to validate the proposed method.