Impedance curve fitting and model validation are critical steps toward experimental data interpretation and electrochemical mechanism study. A mechanistic electrochemical impedance spectra (EIS) model based multi-impedance curve-fitting approach is developed with nonlinear optimization techniques. The mechanistic EIS model consisting of a set of conservation laws is developed using a proton-conducting SOFC button cell (Ni-BZCY7/BZCY7/GBCF) and associated experimental setup as physical bases, which link the multi-physicochemical processes to SOFC impedance responses. A genetic algorithm is employed to determine the model parameters so that the impedance curves predicted by the model match with the experimental data under identical operating conditions. The approach is demonstrated using both the simulated results and the experimental impedance data. Upon the fitting results, modeling study is further performed to interpret the experimental impedance data. Published by Elsevier B.V.