Extracting Quantitative Insights from electrochemical impedance spectra using Statistical Methods
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Abstract
Statistical analysis of electrochemical impedance spec- troscopy data provides a systematic way of detecting changes in electrochemical energy systems. Applying concepts of divergence measures directly on electrochemical impedance spectroscopy data, one can reliably detect and quantify statistically significant changes. The results is a set of high- lighted frequency bands where the measured impedance characteristics differ statistically significantly from a ref- erence curve. The approach is evaluated on a solid-oxide electrolyser cell operated under different conditions and proves to be sensitive to even the smallest changes. The complete numerical implementation and corresponding experimental data are available as supplementary material at https://portal.ijs.si/nextcloud/s/xTa2cmtfxXn2jSz
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divergnece measures, solid-oxide fuel cells, electrochemical impedance spectroscopy, condition monitoring
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