Modeling approach to identify physically distinct processes convoluted in electrochemical impedance spectra for proton-conducting solid oxide fuel cells

Electrochemical impedance spectroscopy (EIS) is an important characterization technique for solid oxide fuel cells (SOFCs); however, the overlap or dispersion in the frequency domain among physically distinct processes imposes great difficulties on unambiguous interpretation of EIS data. Built upon mechanistic SOFC model development and calibrations using polarization curve and multiple EIS curves under different operating voltages, a process reduction strategy was studied to identify both magnitude and frequencies of physically distinct processes convoluted in EIS.