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In the assembling process of proton exchange membrane fuel cell (PEMFC) stack, the clamping load is known to have direct effect on the contact pressure of interfaces. Compression on the membrane electrode assembly (MEA) results in change in gas diffusion layer (GDL), porosity and electrical resistance, thus affecting the performance, durability and reliability of the PEMFC stack. In this paper, the relation between clamping load and performance of PEMFC stack was obtained by experimental study, and the influence of clamping load on the contact pressure of MEAs was analyzed by finite element analysis. The performance test rig was established and the approach of polarization curve testing was introduced. Both the effect of magnitude and distribution of the bolt torques on the performance were taken into account. The finite element model was adopted to figure out the magnitude and uniformity of contact pressure of MEAs, which provides a new angle to understand the experimental results.

Fuel cell vehicles have always garnered a lot of attention in terms of energy utilization and environmental protection. In the analysis of fuel cell performance, there are usually some outliers present in the raw experimental data that can significantly affect the data analysis results. Therefore, data cleaning work is necessary to remove these outliers. The polarization curve is a crucial tool for describing the basic characteristics of fuel cells, typically described by semi-empirical formulas. The parameters in these semi-empirical formulas are fitted using the raw experimental data, so how to quickly and effectively automatically identify and remove data outliers is a crucial step in the process of fitting polarization curve parameters. This article explores data-cleaning methods based on the Local Outlier Factor (LOF) algorithm and the Isolation Forest algorithm to remove data outliers.