Consistency sorting of retired lithium-ion batteries: From the perspective of maximizing remaining useful discharge

Given the promising potential of retired lithium-ion batteries (LIBs) for echelon utilization, enhancing their consistency through effective sorting has become essential. Existing research remains limited to coarse screening, lacking effective experimental validation and quantitative evaluation, failing to meet the grouping requirements. This study presents an integrated framework addressing both verification and evaluation challenges in retired LIB sorting. First, we develop a computational aging method that simulates series module aging behavior by combining cell cycling data under identical operating conditions, circumventing the need for repeated physical regrouping while maximizing data utility. Second, remaining useful discharge (RUD) is proposed as a novel indicator considering long-term degradation evolution, with module RUD utilization rate quantitatively assessing aging consistency. Leveraging these foundations, a rapid battery consistency sorting method based on electrochemical impedance spectroscopy (EIS) is established. The EIS feature, identified through permutation feature importance (PFI) analysis and subsequently dimensionality reduced through principal component analysis (PCA), is combined with greedy sliding window algorithm to enable precise regrouping of retired batteries. This approach achieves superior performance, with average module RUD utilization rate of 87.50 % for 4-series modules and 79.09 % for 7-series modules. This method achieves an optimal trade-off compared to sorting approaches based on remaining capacity and remaining useful life, offering primary advantages in reduced testing time, deterministic regrouping outcomes, and effective mitigation of aging path divergence. The proposed solution injects new impetus into an efficient and economical sorting process in echelon utilization