A comparative study of equivalent circuit model and distribution of relaxation times for fuel cell impedance diagnosis

Electrochemical impedance spectroscopy (EIS) is an important diagnostic tool for fuel cells. Accurate extraction of physical parameters from impedance spectra remains a significant challenge for vehicle fuel cells. The reliability analysis results obtained herein revealed that precise identification of middle and low-frequency impedance by a traditional equivalent circuit model (ECM) was difficult. However, it was determined that the distribution of relaxation times (DRT) could be used to extract three characteristic peaks from the EIS data, which corresponded to the main polarization processes, including gas diffusion, oxygen reduction reaction, and proton transfer. The present work involved the development of a DRT-based EIS reconstruction method for fuel cells. The sensitivity analysis results demonstrated that the designed method enabled the characterization of the gas diffusion impedance and proton transfer impedance at low and high current density, respectively. Notably, these properties could not be accurately determined by a traditional ECM method. The developed approach considerably improved the interpretability of impedance spectra; thus making it applicable for fuel cell fault diagnosis and durability analysis.

Automated summary

Traditional equivalent circuit models face difficulties in accurately identifying mid to low-frequency impedance in fuel cells, but the distribution of relaxation times can extract characteristic peaks corresponding to main polarization processes. A developed method based on relaxation time distribution allows for characterization of gas diffusion and proton transfer impedance at low and high current density, improving the interpretability of impedance spectra.