A Review of Health State Estimation Algorithms for Retired Lithium-ion Batteries

The state of health (SOH) of lithium-ion batteries serves as a crucial indicator of battery performance and reliability, making accurate estimation of SOH essential for enhancing battery longevity. Consequently, this paper categorizes and compares existing SOH estimation methods within the framework of Battery Management Systems (BMS). For instance, the Coulomb counting method is straightforward and intuitive; however, it is disadvantaged by prolonged measurement durations and significant errors. The open-circuit voltage method is uncomplicated and user-friendly, yet it necessitates extended settling times and has a restricted number of evaluation dimensions. Electrochemical impedance spectroscopy offers high accuracy but depends on precise modeling and parameters. The Kalman filter method is precise and exhibits a minor error; however, it necessitates a substantial quantity of data for training and validation. This paper analyzes the advantages and disadvantages of various State of Health (SOH) estimation methods, discusses critical points within the technical field, and offers guidance and recommendations for future research and practical applications of SOH estimation methods.