Enhanced fault detection in polymer electrolyte fuel cells via integral analysis and machine learning

Enhanced fault detection in polymer electrolyte fuel cells via integral analysis and machine learning

Abstract The growing energy demand and population raising require alternative, clean, and sustainable energy systems. During the last few years, hydrogen energy has proven to be a crucial factor under the current conditions. Although the energy conversion process in polymer electrolyte fuel cells (P...

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Bibliographic Details
Main Authors: Ester Melo, Julio Barzola-Monteses, Holguer H. Noriega, Mayken Espinoza-Andaluz
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Energy Informatics
Subjects:
Classification problems
Deep learning models
Fault detection
Machine learning models
PEFC
Online Access:https://doi.org/10.1186/s42162-024-00318-2

Internet

https://doi.org/10.1186/s42162-024-00318-2

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