Optimization and application of the distribution of relaxation times based on characteristic frequency resolution and hyperparameters

Abstract

Distribution of relaxation times (DRT) is a promising method for interpreting electrochemical impedance spectroscopy (EIS) data. Contemporary studies have made significant progress in theory, algorithm, implementation, and application of DRT. However, the DRT deconvolution is often difficult to interpret because of the pseudo-peaks, peaks deviation or peaks overlapping. In this paper, a comprehensive regularization DRT method based on characteristic frequency resolution and hyperparameters is proposed. Based on quantitative analysis of synthetic simulation data, the characteristic frequency resolution optimization is applied to avoid the peaks overlapping and improve the accuracy of DRT. Meanwhile, the hyperparameters optimization which assigns weights to each individual data point is verified to improve the robustness of DRT. Then, the optimized DRT is applied to the EIS experimental data analysis of proton exchange membrane fuel cell (PEMFC), and the polarization processes of PEMFC are identified. Moreover, a fast EIS measurement based on characteristic frequency of DRT is proposed and verified by the impedance prediction which the deviations are within 10%, but the EIS measurement time is shortened from 6 min to 5 s. Moreover, this method can provide a new direction and idea for fault diagnosis based on EIS data, especially for on-board applications.