The fuel cell technologies are advancing and maturing for commercial markets. However proper diagnostic tools needs to be developed in order to insure reliability and durability of fuel cell systems. This paper presents a design of a data driven method to detect CO content in the anode gas of a high temperature fuel cell. In this work the fuel cell characterization is based on an experimental equivalent electrical circuit, where model parameters are mapped as a function of the load current. The designed general likelihood ratio test detection scheme detects whether a equivalent electrical circuit parameter differ from the non-faulty operation. It is proven that the general likelihood ratio test detection scheme, with a very low probability of false alarm, can detect CO content in the anode gas of the fuel cell.
|Publication status||Published - 2015|
|Event||IFAC Safeprocess'15 - Paris, France|
Duration: 2 Sep 2015 → 4 Sep 2015
|Period||02/09/2015 → 04/09/2015|
Bibliographical note9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 Paris, 2–4 September 2015. Edited by Didier Maquin.
- Change detection
- Fault Diagnosis
- PEM Fuel Cell