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

作者：Mohammadi Ali^*; Djerdir Abdesslem; Steiner Nadia Yousfi; Khaburi Davood

来源：International Journal of Hydrogen Energy, 2015, 40(45): 15845-15855.

DOI：10.1016/j.ijhydene.2015.04.157

• Artificial Neural Network
• Fault isolation
• Temperature distribution
• Voltage distribution
• 3D fault sensitive modeling
• Proton exchange membrane fuel cells

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.

• 出版日期2015-12-7