Abstract: Non-destructive testing of lithium-ion batteries(LIBs) by electrochemical impedance spectroscopy(EIS) is an effective method for battery health evaluation and selection. However, when EIS is tested, the charge state(SOC) of batteries needs to be adjusted to a uniform level, which greatly reduces the testing efficiency. Aiming at these problems, a method of EIS curve reconstruction for LIBs based on geometric feature transformation is presented in this study. Firstly, the EIS curve is graphed as a combination of three circular arcs and a straight line, and the characteristic parameters of these geometries are defined. Subsequently, the linear relationship between geometric feature parameters and SOC is established through small-batch EIS test data. Then, the above relationships are transferred to the EIS curve reconstruction of a large number of batteries, and the EIS curve measured under any SOC can be reconstructed to the target SOC. Finally, the proposed method is verified by experiments. The results show that the root-mean-square-error and the average-absolute-percentage-error between the reconstructed EIS curve and the measured EIS curve are controlledby 1.2 mΩ and 3.5%, respectively, and the test time is reduced by at least 98% compared with the traditional methods. The proposed method is simple and easy to implement, and can significantly reduce the measurement time while ensuring the EIS accuracy.

Key words: lithium-ion battery, electrochemical impedance spectroscopy, state of charge, geometric feature, cascade utilization, electric vehicle