Comprehensive diagnosis methodology for faults detection and identification, and performance improvement of Air-Cooled Polymer Electrolyte Fuel Cells

This paper presents a comprehensive practical diagnosis methodology for the detection and identification of faults in Air-Cooled Polymer Electrolyte Fuel Cells (AC-PEFCs). The proper operation of an AC-PEFC depends on many factors to ensure the electrochemical process in the stack and the electricity generation from hydrogen and air. However, the stack performance depends on several factors like state of its cells, stack cooling state, stack operating and non-operating time, hydrogen and air supply pressure, hydrogen and airflow rates, and load demand. So, the diagnosis methodologies development is very helpful as part of the AC-PEFCs advanced monitoring and control systems, and of course for predictive maintenance. The developed diagnosis methodology in this paper can be understood like a diagnosis tree, in the sense that it implies an structured framework tests over the AC-PEFC: hydrogen line, air/cooling subsystem, electrical circuit and even in the stack itself. The developed diagnosis methodology allows to analysis and improving the performance of an AC-PEFC, and consequently its durability, helping to achieve this challenge, perhaps the main, to bring the fuel cells into the market.