Impedance spectroscopy analysis inspired by evolutionary programming as a diagnostic tool for SOEC and SOFC

Abstract

Impedance spectroscopy (IS) is an effective tool for the analysis of solid oxide fuel cell (SOFC) and solid oxide electrolysis cell (SOEC) performance. The challenge using this characterization tool lies within the analysis method. Impedance spectroscopy genetic programming (ISGP) is a novel analysis technique for impedance spectroscopy data. The ISGP utilizes evolutionary programming techniques for finding the most suitable distribution function of relaxation times (DFRT). This approach leads toward a better analysis of impedance spectroscopy results as compared to other analysis tools such as equivalent circuits or deconvolution techniques.

In this work, SOFC and SOEC were examined during operation by IS measurements and the results were analyzed using ISGP. The aim of this work is to show examples of DFRT models which reflect the physical processes occurring during the operation. It is demonstrated that despite the low impedance (in the mΩ range) and the narrow available bandwidth, ISGP can provide consistent DFRT models.


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