Artificial Neural Networks for Aging Simulation of Electrolysis Stacks

Abstract

Abstract This work shows the application of artificial neural networks in terms of modeling and simulating the aging process and the degradation of proton exchange membrane water electrolysis stacks. It includes the training process based on extracted measurement data, the evaluation, and the extrapolation of the network. The fundamentals of the utilized artificial neural network and the training algorithm are clarified. Next, the principle degradation effects are presented as well as the methodology of the underlying measurements. The resulting degradation of the electrolysis stack for different operation conditions is shown.

Topics & Concepts