Study on a novel self-adaptive cathode flow field with deformable baffles for proton exchange membrane fuel cell

Jinping Liu, Zixian Luo, Jianping Hu and Yonghua Cai

Applied Energy, 2025, vol. 377, issue PA, No S0306261924017781

Abstract: The cathode flow field is one of the key influencing factors on the performance of proton exchange membrane fuel cell (PEMFC). Current research on the cathode flow field mainly focuses on specific current density conditions, without considering the performance of the flow field within the entire current density range. Therefore, this study presents a cathode self-adaptive flow field with deformable baffles and its design method, and optimizes the parameters of the baffles through neural network and genetic algorithm. Results indicate that PEMFC with a cathode self-adaptive flow field can achieve a wider range of operating current density. PEMFC with a cathode self-adaptive flow field demonstrates increased net power density across various current densities ranging from 0.2 to 3.0 A·cm−2 compared to PEMFC with the traditional straight channel flow field. At current density of 3.0 A·cm−2, the power density of PEMFC with the adaptive flow field is approximately 19 % higher than that of PEMFC with the straight channel flow field. The enhancement magnitude and trend of the experimental results are generally consistent with the numerical simulation results.

Keywords: Self-adaptive flow field; Baffle; Optimization; Neural network; Genetic algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.124395

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