In order to solve the problems of differential evolution algorithm, such as easily falling into the local optimum and the identification accuracy needs to be optimized, the improved algorithm introduces the random walk strategy based on the original selection, mutation and cross operation, which enhances the local search ability of the algorithm and improves the diversity of the population. In this paper, based on the measured and predicted values of equivalent series resistance (ESR) and equivalent impedance (Z), the objective function is constructed, and the improved algorithm is used to optimize the objective function. The parameters of two electrolytic capacitor models with different complexity are identified, and the results of parameter identification and the predicted values of ESR and impedance Z are obtained. Simulation results show that the improved algorithm is effective, and the prediction accuracy of the improved algorithm under the classical model is always 5% better than that of the traditional algorithm, which can improve the monitoring accuracy of the electrolytic capacitor.