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

Yasser Diab*, Francois Auger, Emmanuel Schaeffer, Stéphane Chevalier, Adib Allahham

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
22 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number2337
Number of pages23
JournalEnergies
Volume15
Issue number7
DOIs
Publication statusPublished - 23 Mar 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • discretized dynamic model
  • dynamic operating conditions
  • extended Kalman filter
  • PEMFC parameters
  • real-time estimation
  • state of health

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