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LPV Model-Based Fault Diagnosis Using Relative Fault Sensitivity Signature Approach in PEM Fuel Cell
Puig Cayuela, Vicenç; Quevedo Casín, Joseba Jokin; Lira Ramírez, Salvador de
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
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 Nexa c 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.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
Informatica
Control automàtic -- Congressos
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
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