Lithium-ion Second-Life Batteries: Aging Modeling and Experimental Validation

Re-utilizing lithium-ion batteries from electric vehicles reduces their environmental impact. To ensure their optimal sizing and safe use, identifying the current state of the battery and predicting its remaining useful life is essential. This work analyzes the degradation mechanisms involved and proposes an aging model that utilizes a semi-empirical approach to accurately reproduce the battery's state of health within a range of 75-45 %. Calendar aging includes dependencies on temperature and state of charge while cycling aging is modeled based on depth of discharge, medium SOC, temperature, and Crate. The model is validated against experimental data from 14 LMO/LNO cells previously used in actual Nissan Leaf vehicles and an RMSE bellow 2.5% is achieved in every case.