Fourier neural operators enhanced with physics guided loss for modeling fuel cell degradation and lifetime forecasting
Ali Egemen Ener, Batuhan Cinar, Bugra Eyidogan, Muhammed Enis Sen et autres
Abstract Reliable lifetime forecasting of proton-exchange membrane fuel cells (PEMFCs) is essential for durable hydrogen-energy systems, yet degradation dynamics are nonlinear, regime-dependent, and difficult to model efficiently at scale. We propose a physics-guided Fourier Neural Operator (FNO) for voltage degradation forecasting and …
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Scientific Reports