A high-precision model for large active area proton exchange membrane fuel cells incorporating aggregate modeling and multi-parameter verification

Kai Han, Xiaolong Li, Min Fan, Lei Yang, Zhaojing Ni*

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摘要

In proton exchange membrane fuel cells (PEMFCs) with large active areas, uneven distributions of reactants (e.g., water and oxygen) and electrochemical parameters (e.g., local current density) significantly affect performance, particularly under low stoichiometric ratios and high current densities. To address these issues, this study introduces a high-precision three-dimensional model integrating aggregate modeling with multi-parameter verification. The model accurately predicts key metrics such as hydrogen permeation current density and pressure differentials, with maximum deviations of 0.07 mA/cm2 and 0.64 kPa, respectively. Validation against segmented PEMFC experimental data demonstrates excellent agreement for output voltage, ohmic overpotential, and activation overpotential, with maximum relative errors of 1.0 %, 8.5 %, and 1.2 %, respectively. The study further reveals that ohmic and activation overpotentials may compensate for each other, improving polarization curve accuracy and underscoring the necessity of thorough verification of these parameters. Additionally, the model captures the linear-to-exponential growth of the non-uniformity index of local current density (σ) with increasing current density, while demonstrating that higher pressure, temperature, stoichiometric ratios, and cathode humidity significantly reduce σ, especially under high current density conditions. These findings highlight the model's strong predictive capabilities and its value for optimizing PEMFC performance through detailed internal physical field analysis.

源语言英语
文章编号236106
期刊Journal of Power Sources
630
DOI
出版状态已出版 - 28 2月 2025

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引用此

Han, K., Li, X., Fan, M., Yang, L., & Ni, Z. (2025). A high-precision model for large active area proton exchange membrane fuel cells incorporating aggregate modeling and multi-parameter verification. Journal of Power Sources, 630, 文章 236106. https://doi.org/10.1016/j.jpowsour.2024.236106