Detection of lithium plating based on the distribution of relaxation times

Lithium plating leads to severe capacity fading and possible safety problems in lithium-ion batteries (LiB). Therefore, it is necessary to provide an in-situ detection methodology of lithium plating evolution during battery cycling. Qualitative analysis of the Distribution of Relaxation Times (DRT), based on Electrochemical Impedance Spectroscopy (EIS) deconvolution, shows a different degradation mechanism between lithium plating and normal aging batteries. A Support Vector Machine (SVM) detection algorithm based on the DRT is proposed. It only relies on the measured capacity and EIS data during battery aging, which is also easy to process and non-destructive to battery sample. The method has a significant advantage in battery safety management and echelon selection of retired batteries.