Integrated deep stacked autoencoder–BiLSTM networks and online geometric electrochemical impedance spectroscopy data for real-time fault diagnosis and health assessment of PEMFCs

Applied Energy 2026

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Authors: Pezhman Bayat, Pezhman Bayat, Peyman Bayat, Peyman Bayat
DOI: 10.1016/j.apenergy.2026.127602
Cited by: 2
References: 27

Fields of Study & Subjects

Fuel Cells and Related Materials Electrocatalysts for Energy Conversion Advanced battery technologies research

Publication details

Journal / source
Applied Energy
Publisher
Elsevier BV
Volume
411
Pages
127602–127602
Publication date
7 March 2026
Language
EN