LPV model-based fault diagnosis using relative fault sensitivity signature approach in a PEM fuel cell
Document typeConference report
PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessRestricted access - publisher's policy
In this paper, a model-based fault diagnosis methodology for PEM fuel cell systems is presented. The methodology is based on computing residuals using a LPV observer. Fault detection is based on using adaptive threshold generated using an interval observer. Fault isolation is performed using the Euclidean distance between observed relative residuals and theoretical relative sensitivities. To illustrate the results, the commercial fuel cell Ballard Nexac is used in simulation where a set of typical fault scenarios have been considered. Finally, the diagnosis results corresponding to those fault scenarios are presented. It is remarkable that with this methodology it is possible to diagnose and isolate all the considered faults in contrast with other well known methodologies which use the classic binary signature matrix approach.
Citationde Lira, S. [et al.]. LPV model-based fault diagnosis using relative fault sensitivity signature approach in a PEM fuel cell. A: Mediterranean Conference on Control and Automation. "18th. Mediterranean Conference on Control and Automation". Marrakech: IEEE Press. Institute of Electrical and Electronics Engineers, 2010, p. 1284-1289.
- SAC - Sistemes Avançats de Control - Ponències/Comunicacions de congressos 
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos 
- IRI - Institut de Robòtica i Informàtica Industrial, CSIC-UPC - Ponències/Comunicacions de congressos 
|drac today.pdf||425,9Kb||Restricted access|