A Review of State-of-health Estimation of Lithium-ion Batteries: Experiments and Data

Accurate state-of-health (SOH) estimation of Lithium-ion batteries (LIBs) is crucial for Battery Management System (BMS) in electric vehicles (EVs). To develop a practical SOH estimation matched with high precision, experimental data, battery model and estimation algorithm are indispensable aspects to be well handled. Recently, review of battery model and estimation algorithm has been well presented to provide references for the world academic community. In this paper, we focus on the review of experiments and data. Three types of experiment modes with the experimental variables and generated data are reviewed and analyzed in this paper: charging-discharging mode, discharging mode and charging mode. Based on the concrete analysis of experiments and data, we find that experiment modes and variables affect SOH estimation uniquely. The work provides a new method to study SOH, which is helpful to simplify research and reduce battery experiments.