A computationally efficient and high-fidelity 1D steady-state performance model for PEM fuel cells

Abstract

Abstract The performance of a proton exchange membrane (PEM) fuel cell is determined by many factors, including operating conditions, component specifications, and system design, making it challenging to predict its performance over a wide range of operating conditions. Existing fuel cell models can be complex and computationally demanding or may be over-simplified by neglecting many transport phenomena. Therefore, a high-fidelity and computationally efficient model is urgently needed for the model-based control of fuel cells. In this study, semi-implicit multi-physics numerical models have been established, taking the mass, momentum, reactants, liquid water, membrane water, electrons, ions, and energy in all fuel cell components into account. The developed 1D model is of high fidelity by incorporating the two-phase flow, non-isothermal effect, and convection, and is still computationally efficient. These models are validated against data from an auto manufacturer with good agreements, and the computing efficiency is evaluated on a modest laptop computer. The modeling results suggest that the two-phase flow model exhibits better prediction accuracy than the single-phase flow model when reactants are fully humidified, while under low humidity conditions, the two models present equivalent performance as liquid water does not exist in the fuel cell components. The results also suggest that the maximum convective/diffusive ratio of H2, O2, and vapor mass fluxes can be 12%, 5.3%, and 35%, respectively, which are ignored in most diffusion-dominant models. The developed models are computationally efficient, requiring only 0.56 s and 0.26 s to simulate a steady-state operation of fuel cells for the two- and single-phase flow models, respectively. This implies that the developed models are suitable for the control of PEM fuel cells.