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Model-based aging tolerant control with power loss prediction of Proton Exchange Membrane Fuel Cell
- Source :
- International Journal of Hydrogen Energy, International Journal of Hydrogen Energy, Elsevier, 2018, International Journal of Hydrogen Energy, 2020, 45 (19), pp.11242-11254, International Journal of Hydrogen Energy, Elsevier, 2020, 45 (19), pp.11242-11254
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- International audience; Proton Exchange Membrane Fuel Cells are promising energy converters that allow powering vehicles or buildings in a clean manner. Nevertheless, their performance are affected by faults and irreversible degradation mechanisms that are far from being fully understood. Consequently, during the last decade, researches have been conducted on the diagnostic of faults of this promising converter. Nevertheless, aging was never the subject of a particular attention concerning control. As a result, this paper proposes an aging tolerant control strategy for Proton Exchange Membrane Fuel Cells. It aims at generating the load current reference taking the state of health into account. Moreover, using a model inversion of an Energetic Macroscopic Representation with time-varying parameters, the coherent references of input flows of gas can be calculated. Finally, the paper details a method to identify and predict the maximum power the fuel cell is able to provide at present time based on a Maximum Power Point Tracking algorithm. Also this algorithm aims at forecasting the Remaining Useful Life for a given power reference. This method is validated on a simulation case.
- Subjects :
- [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering
[SPI.NRJ]Engineering Sciences [physics]/Electric power
[PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph]
[PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph]
ComputingMilieux_MISCELLANEOUS
[SPI.AUTO]Engineering Sciences [physics]/Automatic
Subjects
Details
- Language :
- English
- ISSN :
- 03603199
- Database :
- OpenAIRE
- Journal :
- International Journal of Hydrogen Energy, International Journal of Hydrogen Energy, Elsevier, 2018, International Journal of Hydrogen Energy, 2020, 45 (19), pp.11242-11254, International Journal of Hydrogen Energy, Elsevier, 2020, 45 (19), pp.11242-11254
- Accession number :
- edsair.dedup.wf.001..78fcff6ed2f22c263a57a82be8f5cd81