A method for estimating the health status of lithium-ion batteries based on electrochemical impedance spectroscopy

Abstract Driven by the booming electric vehicle market, lithium-ion batteries are experiencing an increasingly strong demand. As demand for lithium-ion batteries grows, accurately determining their state of health (SOH) has become a critical step in supporting the dependable and efficient operation of battery technologies. At present, SOH estimation methods mainly rely on data such as current and voltage, which are easily affected by working conditions and require a relatively long data measurement time. The electrochemical impedance spectrum that can be obtained through a relatively short period of measurement when the battery is in a static state not only overcomes the above problems but also contains rich aging information, thus becoming a new method for accurately estimating the SOH of lithium-ion batteries. A novel approach is introduced in this study to evaluate the health status of lithium-ion batteries using electrochemical impedance spectroscopy (EIS). The real part, imaginary part, amplitude, and phase of EIS data are extracted as features to construct a battery health state estimation model combining BiLSTM and SVM models. This method utilizes the characteristics of EIS and takes into account the advantages of long-term memory and small sample generalization of the fusion model. Experimental findings indicate that the mean absolute percentage error (MAPE) between the predicted and actual SOH values is under 3 %, confirming the reliability of the proposed EIS-based estimation approach.