Impedance Modeling and Aging Research of the Lithium-Ion Batteries Using the EIS Technique

As the core component of electric vehicles (EVs), batteries attach increasingly general attention along with the rapid expansion of electric vehicle market. Battery performance effect directly the safety and reliability of the EVs, so its managing technologies are more and more crucial. Among them, the methods of estimating the state of health (SoH) and predicting remaining useful life become the focuses, which are essential to ensure their dependability and optimum performance over time. This paper mainly focuses on impedance modeling and aging research (aging diagnosis and life prediction) of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS) technique is used to obtain impedance characteristic of batteries. On the one hand, equivalent circuit modeling (ECM) can be motivated by EIS, with the goal to fit measured impedance data using circuit elements. On the other hand, the aging research of batteries can be analyzed using the resistance information provided by EIS due to the correlation between battery resistance and lifetime. The possible causes of battery aging are analyzed based on changes in the impedance spectrum, which are obtained under different life conditions through an accelerated life experiment. According to the result and the corresponding electrode process, an improved Randels model is then established. Furthermore, a method to predict the battery life based on EIS is proposed. The battery life characterization parameters and calculation methods are defined according to related test manuals and standards. Then, the impedance amplitude of a certain frequency is selected as an estimation parameter. Finally, the first-order polynomial is selected as the fitting function comparing with the fitting results of various functions.