Hydrophobicity gradient optimization of fuel cell gas diffusion media for its application in vehicles

Yang, Qinwen; Zhang, Zhen; Xiao, Gang; Xue, Deyi

doi:10.1016/j.fmre.2024.01.007

Fundamental Research

2024

DOI: 10.1016/j.fmre.2024.01.007

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Hydrophobicity gradient optimization of fuel cell gas diffusion media for its application in vehicles

Qinwen Yang,

Zhen Zhang,

Gang Xiao

et al.

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Cited by 2 publications

References 44 publications

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Machine learning-assisted design of flow fields for proton exchange membrane fuel cells

Zhou,

Zhang,

Feng

et al. 2025

Journal of Power Sources

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Machine learning-assisted design of flow fields for proton exchange membrane fuel cells

Zhou,

Zhang,

Feng

et al. 2025

Journal of Power Sources

View full text Add to dashboard Cite

Clamping Pressure and Catalyst Distribution Analyses on PEMFC Performance Improvement

Yang,

Wang,

Xiao

2024

Energies

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The coupling effects of clamping pressure and catalyst distribution are comprehensively considered to improve proton exchange membrane fuel cell (PEMFC) performance. Numerical models were constructed to study the performance changes and the corresponding internal states of PEMFC under different clamping pressures. Since the increased clamping pressure reduces the uniformity of current density, non-uniform designs with decreased catalyst loading under channel and increased catalyst loading under rib are proposed for performance improvement. A weighted objective function considering current density magnitude and uniformity was constructed, and the performances of different catalyst loading distributions were analyzed. Compared to the uniform distribution, the optimized distribution with a variation of −15% and 15% under channel and rib had the maximum objective function value of 17.24%. The deformation analysis of the gas diffusion layer and optimization of catalyst loading distribution based on deformation analysis provided a reference for the assembly of PEMFC and the production of MEA.

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Hydrophobicity gradient optimization of fuel cell gas diffusion media for its application in vehicles

Cited by 2 publications

References 44 publications

Machine learning-assisted design of flow fields for proton exchange membrane fuel cells

Machine learning-assisted design of flow fields for proton exchange membrane fuel cells

Clamping Pressure and Catalyst Distribution Analyses on PEMFC Performance Improvement

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