Data-efficient and interpretable long-term prognostics of PEMFC degradation via physics-constrained symbolic regression–physics-informed neural network

eTransportation 2026

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Authors: Wenchao Zhu, Bowen Xu, Bingxin Guo, Changjun Xie, Rui Xiong

DOI: 10.1016/j.etran.2026.100615

Cited by: 14

References: 59

Fields of Study & Subjects

Fuel Cells and Related Materials Electrocatalysts for Energy Conversion Machine Learning and ELM

References 59