An Electrode Aging Information-Embedded Rapid Sorting Approach for Second-Life Applications of Lithium-Ion Batteries Retired from Electric Vehicles

Reusing lithium-ion batteries retired from electric vehicles with high available capacities for second-life applications has been recognized with tremendous economic and environmental benefits. Although implementable, it leaves a critical challenge in sorting retired batteries with discrepant characteristics accurately and efficiently. In this study, we propose three novel electrode aging parameters to characterize battery aging behaviors at both electrode level and cell level and develop an electrode aging information-embedded rapid sorting approach based on constant-current charging data. Unlike conventional capacity test-based sorting approaches, the proposed method provides in-depth insights into battery aging behaviors, reduces test time within 1 h, and supports module/pack-level tests to further alleviate experimental costs. The simulation results indicate the promising performance of the proposed method, where all the retired batteries show great homogeneity in their respective groups with the standard deviations of less than 14 mAh in capacity and 1.8% in SOH.