A Multi-Stage Cell Grouping Method for Retired 18650 Ternary Lithium-Ion Batteries Based on Serpentine Sorting

The second-life utilization of retired power batteries is critically constrained by high cell-to-cell variability in capacity and internal resistance, which severely reduces the usable capacity of repacked modules. To overcome this challenge, this paper presents a multi-stage screening and grouping strategy that balances accuracy with practical efficiency. The method comprises four progressive steps: static Euclidean distance-based pre-screening, 0.1C low-rate reference capacity calibration, 0.5C operating-condition re-screening, and serpentine sorting for final grouping. A total of 389 retired 18650 ternary lithium-ion batteries from a single batch were studied. First, 89 cells were pre-screened using voltage–internal resistance Euclidean distance, from which 16 cells were selected for 0.1C calibration to establish a low-rate reference capacity baseline. Subsequently, 52 cells were re-screened from the remaining 300 and tested at a 0.5C rate. Finally, the 52 cells were assembled into 13 groups via serpentine sorting and uniformly calibrated to 50% SOC. A benchmark conversion coefficient β, defined as the ratio of the mean 0.5C capacity to the mean 0.1C capacity, and a comprehensive consistency index (CQI) were established for evaluation. Results show that the mean 0.1C capacity is 2835.2 mAh with β = 0.9681. After serpentine grouping, the capacity range across the 13 groups is only 16.69 mAh, with a coefficient of variation of 0.0407%—significantly outperforming random grouping—and the CQI reaches 0.985. The proposed method reduces the total capacity testing time from approximately 21.9 days to about 2.5 days, improving efficiency by approximately 88%. In contrast to prior work focusing solely on algorithmic improvements, this study, for the first time, integrates static outlier exclusion, small-sample-rate mapping, and serpentine balanced grouping into a closed-loop engineering workflow, providing a deterministic, rule-based solution for the entire screening-to-grouping pipeline in second-life applications. The method requires neither complex instrumentation nor sophisticated algorithms and exhibits strong robustness against common measurement errors, offering an economical, reliable, and easily replicable engineering solution for retired battery second-life utilization.