Model based fault detection and isolation for a PEM Fuel Cell System

Abstract

Fuel cell systems are considered as clean and efficient power sources, which are under development by manufacturers for both stationary and mobile applications. Polymer Electrolyte Membrane (PEM) fuel cells are considered to have the highest energy density due to the nature of the reaction and the quickest start up time (≤1 sec). These are the main reasons for being used in applications such as automotive engines, portable and backup power applications. Recent years have seen the proliferation of PEM fuel cell system (PEMFCs)optimization and control applications, where the aim is to obtain a better process performance. Nowadays, increases in safety, reliability and uptime process operation are requiring the inclusion of fault diagnosis algorithms. Because of the lack of space for physical redundancy and cost reduction in automotive applications, the automotive industry is pushing and facing better techniques for fault diagnosis that makes its products compatible in the markets offering to the final customer not only the best quality but also a reliable product. Here an alternative technique to hardware redundancy is the analytical redundancy which uses a mathematical model with input and output measurements as a monitored system signals to generate a fault diagnosis. Analytical redundancy could also allow increasing the fault tolerance, using the recent methods of Fault Tolerant Control (FTC).