Numerical study and prediction of water transport through a PEM fuel cell based on genetic algorithm

Jun Shen, Chenshuo Zhang, Longjian Li, Sichen Liu, Haobo Liu, Ben Chen and Changqing Du

Energy, 2024, vol. 308, issue C

Abstract: Water management is important to achieve excellent performance and durability of proton exchange membrane fuel cells (PEMFCs). Due to the complexity of the two-phase water transport process, a rapid assessment of the water transport characteristics inside the fuel cell is essential for its stable operation. Based on the dynamic equilibrium process of water transfer and the relationship between the membrane water content and the water saturation in the gas phase, a multi-state water transport model is proposed to quickly evaluate and quantitatively analyze the net water transport characteristics based on genetic algorithm. The results indicate that the water produced by the electrochemical reaction can be partially removed through the anode at low current densities and relative humidity. The proportion of water removed through the anode decreases with the increase of anode relative humidity, current density, temperature, membrane thickness, and the decrease of back pressure. Considering the effect of water transport on cell performance, it's found that membrane dehydration and a significant increase in ohmic loss are the main reasons for the performance degradation at high temperatures, and the attenuation could be mitigated by cathode humidification. Quantitative analysis of water transport guides the formulation of efficient water management strategies of PEMFC.

Keywords: PEMFC; Water transport; Genetic algorithm; Ohmic loss; Quantitative analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:308:y:2024:i:c:s0360544224026252

DOI: 10.1016/j.energy.2024.132851

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