Proton Exchange Membrane Fuel Cell Prognosis Based on Frequency-Domain Kalman Filter

The degradation seriously affects the durability and cost of the proton exchange membrane fuel cell (PEMFC). This article presents a novel model-driven method based on the frequency-domain Kalman filter (FDKF) and voltage degradation model to predict the degradation of PEMFC in the frequency domain....

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Bibliographic Details
Published in:IEEE transactions on transportation electrification 2021-12, Vol.7 (4), p.2332-2343
Main Authors: Ao, Yunjin, Laghrouche, Salah, Depernet, Daniel, Chen, Kui
Format: Article
Language:English
Subjects:
Accuracy
Automatic
Computational modeling
Data models
Degradation
Degradation prognosis
Electric power
Engineering Sciences
Extended Kalman filter
Fluid mechanics
Frequency domain analysis
frequency-domain Kalman filter (FDKF)
Fuel cells
Load modeling
Mechanics
model-driven method
Physics
Predictive models
Prognosis
Prognostics and health management
proton exchange membrane fuel cell (PEMFC)
Proton exchange membrane fuel cells
Protons
Thermics
voltage degradation model
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Summary:The degradation seriously affects the durability and cost of the proton exchange membrane fuel cell (PEMFC). This article presents a novel model-driven method based on the frequency-domain Kalman filter (FDKF) and voltage degradation model to predict the degradation of PEMFC in the frequency domain. The advantage of the proposed FDKF method is that it can process the data in groups; thus, the computation time can be greatly reduced with high accuracy. Two degradation experiments under constant and quasi-dynamic currents have been used to demonstrate its prognosis performances under different conditions and different training times. Compared with the traditional time-domain extended Kalman filter method and literature, it has been demonstrated that the proposed one has higher accuracy and requires much less calculation time.
ISSN:2332-7782
2577-4212
2332-7782
DOI:10.1109/TTE.2021.3077506