Diagnosis of CO Pollution in HTPEM Fuel Cell using Statistical Change Detection

Christian Jeppesen, Mogens Blanke, Fan Zhou, Søren Juhl Andreasen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)
302 Downloads (Pure)

Abstract

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.
Original languageEnglish
Title of host publication9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015
EditorsSukumar Mishra
Number of pages7
Volume48
Publication dateSep 2015
Edition21
Pages547-553
DOIs
Publication statusPublished - Sep 2015
Event9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Paris, France
Duration: 2 Sep 20154 Sep 2015
Conference number: 9

Conference

Conference9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Number9
Country/TerritoryFrance
CityParis
Period02/09/201504/09/2015
SeriesIFAC-PapersOnLine
ISSN1474-6670

Keywords

  • Change detection
  • GLRT
  • Fault Diagnosis
  • PEM fuel cell
  • HTPEM
  • EIS
  • Electrochemical Impedance Spectroscopy

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