A quasi-2D multiphase flow proton exchange membrane fuel cell model for efficient distributed cell state prediction

Abstract

To enhance the durability and performance of proton exchange membrane fuel cells, it is essential to capture both spatial and temporal variations of internal states during dynamic operation. While existing reduced-order models (0D/1D) lack spatial resolution, 3D models are often too computationally expensive for transient simulations. To bridge this gap, we present a quasi-2D, time-dependent multiphase model capable of predicting distributed cell states with high computational efficiency. The model accounts for key transport phenomena, including convection, multicomponent diffusion, capillary effects, and membrane water dynamics via electro-osmotic drag and diffusion. It also includes nitrogen crossover, finite-rate sorption/desorption at membrane interfaces, and heat generation from electrochemical reactions, proton conduction, and phase change. A linearisation scheme combined with Chebyshev collocation ensures low computational cost and near real-time capability. Validation against high-resolution 3D computational fluid dynamics simulations confirms the model's accuracy in predicting polarisation curves, gas species distributions, liquid water accumulation, and temperature profiles. Dynamic simulations under load transients further demonstrate its ability to capture key physical processes, underpinning the importance of spatially resolved water transport. By enabling fast and accurate simulations of both steady-state and dynamic fuel cell behaviour, the proposed model supports extensive parametric studies, control system development, and predictive diagnostics. Its computational efficiency makes it a valuable tool for improving fuel cell efficiency, longevity, and system-level control strategies.