Aging Effect–Aware Finite Element Model and Parameter Identification Method of LithiumIon Battery

Abstract

Battery aging is an inevitable macroscopic phenomenon in the use of the battery, which is characterized by capacity decline and power reduction. If the charging and discharging strategy does not adjust with the aging state, it is easy to cause battery abuse and accelerate the decline. To avoid this situation, the aging model with consideration of the battery degradation is coupled into the pseudotwodimensional (P2D) model. An aging effectaware finite element model that can describe battery physical information accurately is presented in this article. The model parameters are divided into four parts: structure parameters, thermodynamic parameters, kinetic parameters, and aging parameters. The identification experiments are designed based on the characteristics of these types of parameters. The decoupling and parameter identification methods of kinetic parameters according to the response characteristics of each parameter under specific excitation, and stateofcharge (SOC) partitioned range identification technology of aging parameters is proposed and verified. Finally, the aging effectaware model and the identification parameters are verified under constant current (CC) and different dynamic conditions with different charge rate (Crate). The ability of the proposed model to track the aging trajectory in the whole life cycle is verified under various cycle conditions. The proposed model can be applied to aging mechanism analysis and health management from point of inner properties of the batteries.