An electrochemical-thermal-aging effects coupled model for lithium-ion batteries performance simulation and state of health estimation

Numerous interrelated coupled aging mechanisms contribute to the degradation of lithium-ion batteries (LIBs), making it challenging to confirm the influence of aging effects on the performance and state of health (SOH). Inspired by electrochemical impedance spectroscopy (EIS) analysis and observed morphological changes, this paper considers double layer resistance increase, solid electrolyte interface (SEI) film growth, and cathode aggregate crack propagation as the main aging effects, and the influence of temperature is considered, leading to development of an electrochemical-thermal-aging coupled model. The model achieves high-precision simulation for different temperature and aging conditions by updating the model parameters based on the aging effects and internal temperature. Compared with experimental data, the relative error of voltage simulation is within 1%. Additionally, the aging effects parameters exhibit a consistent trend with data analysis and mechanism inference, and this strong correlation is beneficial for estimating SOH. The estimation error of SOH based on four linear regression methods is less than 0.5%. This novel electrochemical-thermal-aging effects coupling model addresses two major challenges in battery management system (BMS): performance simulation and SOH estimation under real-world operating conditions.