Communication Dans Un Congrès Année : 2021

PEMFC state-of-health estimation using a model-based state Bayesian observer under an automotive load profile

Résumé

An estimation of the actual State of health (SoH) of the Proton Exchange Membrane Fuel Cell (PEMFC) based on a Bayesian observer model is presented. The observer model considers a degradation model which describes the electrodes platinum dissolution to characterize the energy source deterioration under dynamic operation conditions in real time. This observer model is carried out using an Unscented Kalman Filter to correct and update the SoH estimation. The proposed method is evaluated using a 1000h durability test under a dynamic highly load profile, similar to an automotive load cycling, from a 20 cells PEMFC stack.
Fichier non déposé

Dates et versions

cea-04833372 , version 1 (12-12-2024)

Identifiants

Citer

Andres Jacome, Daniel Hissel, Vincent Heiries, Mathias Gerard, Sebastien Rosini. PEMFC state-of-health estimation using a model-based state Bayesian observer under an automotive load profile. 2020 IEEE Vehicle Power and Propulsion Conference (VPPC), Nov 2020, Gijon, Spain. pp.1-4, ⟨10.1109/VPPC49601.2020.9330963⟩. ⟨cea-04833372⟩
26 Consultations
0 Téléchargements

Altmetric

Partager

More