Thermal Fault Diagnosis Method for Lithium-ion Batteries Based on Electrochemical Impedance Spectroscopy

Lithium-ion batteries have significant advantages in cost, performance, and environmental protection due to their advantages of being reusable and having high energy density. However, the frequent safety accidents of lithium batteries, especially the problems of battery combustion and explosion caused by thermal faults, seriously restrict the development and application of lithium batteries. This paper proposes a method for diagnosing thermal faults in lithium batteries, using the characteristic peak points of the Distribution of Relaxation Times (DRT) curve based on Electrochemical Impedance Spectroscopy (EIS) data as diagnostic indicators. The DRT curve of the battery is constructed using the Tikhonov regularization method based on Radial Basis Function (RBF), and the coordinates of the DRT characteristic peak points are classified using K-means clustering algorithm to diagnose and distinguish thermal abnormal batteries. This method does not require the deployment of temperature sensors, nor does it rely on complex mathematical models or large amounts of historical data. The established experimental platform was used for verification, and the outcome indicate that this strategy can effectively identify thermal abnormal batteries in a battery pack consisting of 26 battery cells.