Impedance Analysis and Parameter Estimation of Lithium-Ion Batteries Using the EIS Technique

Estimating the parameters of lithium-ion (Li-ion) batteries under dynamic working conditions is a critical challenge in the health management of electrical energy storage systems. This paper estimates the equivalent circuit model (ECM) parameters and analyzes the influence of different factors on the Li-ion batteries impedance using the electrochemical impedance spectroscopy (EIS) technique. Firstly, the influence of the temperature, state of charge (SOC) and number of charging/discharging cycles on the impedance spectrum was studied. Nyquist plots were used to perform this analysis. Subsequently, ECMs were used to characterize the Li-ion batteries under study at different operating conditions. Specifically, the ECM parameters were estimated using the gaining-sharing knowledge (GSK) metaheuristic algorithm, allowing the consequent estimation of the impedance spectra obtained by the EIS technique. Experimental results included 15 datasets measured experimentally at three temperature levels for five SOCs and different number of charging/discharging cycles. To investigate the variation of Li-ion battery parameters with cyclic aging 350 datasets from the literature were also used. The results showed that the impedance and model parameters depend considerably on the considered factors. The estimation of the ECM parameters demonstrated high accuracy and reliability (mean RMSE values of 4.32E-02 and 2.33E-02 and mean STD values of 3.38E-16 and 5.82E-13 with measured and literature datasets, respectively), allowing the robust determination of the numerous impedance spectra under study.