Quantitative Relationship Analysis of Fuel-Cell Evaluation Equipment Variables: A Pearson-Spearman-Kendall Methodology

초록

This study presents a quantitative framework for analyzing test-bench, facility, and environmental variables from fuel-cell test-bench data. Of 200+ channels, 29 variables were grouped into controlled, pressure–temperature, and lab/external streams. After detecting load steps, anomalies, and skewed distributions via line plots and histograms, IQR-based outlier removal and standardization were applied. Dependency analysis using Pearson’s r, Spearman’s ρ, and Kendall’s τ revealed that stack voltage is a complex function of load, supply pressure, and coolant-outlet temperature, that control-system variables exhibit near-perfect rank agreement, and that environmental variations significantly affect pressure and flow stability. Overall, this methodology provides essential data for real-time anomaly detection and operational-logic optimization in fuel-cell evaluation equipment. © The Korean Institute of Electrical Engineers

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