Real-Time Estimation of PEMFC Parameters Using a Continuous-Discrete Extended Kalman Filter Derived from a Pseudo Two-Dimensional Model

Yasser Diab (1) , François Auger (1) , Emmanuel Schaeffer (1) , Stéphane Chevalier (2) , Adib Allahham (3)

1 IREENA - Institut de Recherche en Energie Electrique de Nantes Atlantique UR 4642
2 I2M - Institut de Mécanique et d'Ingénierie
3 Newcastle University [Newcastle]

Proton Exchange Membrane Fuel Cells (PEMFCs) are clean energy conversion devices that are widely used in various energy applications. In most applications, the main challenge is accurately estimating the state of health (SoH) of the PEMFCs during dynamic operating conditions. Moreover, their behavior is affected by numerous physical phenomena such as heat and membrane flooding. This paper proposes the design of an observer to estimate the PEMFC parameters. A state-space model is first built from 2D physical equations solved by a finite difference in a discretized space domain. The discretized dynamic model is then used to design an observer based on the continuous-discrete extended Kalman filter. The observer has been validated experimentally and is used to estimate the parameters of a PEMFC under dynamic operating conditions. For several load variations, the results obtained using the proposed observer accurately characterize the dynamic responses of PEMFC in real-time.

Mots clés: PEMFC parameters; discretized dynamic model; dynamic operating conditions; extended Kalman filter; real-time estimation; state of health

Domaines: Traitement du signal et de l'image [eess.SP]

Yasser Diab, François Auger, Emmanuel Schaeffer, Stéphane Chevalier, Adib Allahham. Real-Time Estimation of PEMFC Parameters Using a Continuous-Discrete Extended Kalman Filter Derived from a Pseudo Two-Dimensional Model. Energies, 2022, 15 (7), pp.2337. ⟨10.3390/en15072337⟩. ⟨hal-04074631⟩