Advanced diagnosis based on temperature and current density distributions in a single PEMFC

The present study focuses on developing a reliable fault identification and localisation tool for Proton Exchange Membrane Fuel Cell (PEMFC). This diagnosis tool relies on 2 steps: first, a 3D model for a single PEMFC, that allows estimating local parameters (temperature, current and voltage distributions within the single cell). An experimental set-up allows reliable monitoring of different parameters used by the model to estimate the current density distributions over the 3D space zones of the cell. Furthermore, this 3D fault-sensitive model allows to simulate faults linked to poor water management (drying out and flooding) with 2 severity levels (''flooding'', ``drying'', ``high flooding'' and ``high drying''). Then, the second step consists of developing a two-layer feed-forward ANN that has been with an adapted database to localize each fault within the different segments of the single cell. The results show good recognition and localization rate for the considered fault, which allows to conclude that this approach is very promising for fault localization, which is one of the key points regarding diagnosis. Copyright (C) 2015, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.