Fast and Non-Destructive Screening of Reused LIB Packs Using CAN Data and Dual-Rate Correction Models

In this study, we propose a fast and non-destructive screening method for evaluating the State of Health (SOH) of reused lithium-ion battery (LIB) packs retired from electric vehicles. Conventional methods require time-consuming disassembly and low-rate (0.2C) charge/discharge tests per module, leading to significant labor and safety concerns.Our method utilizes in-vehicle CAN data (voltage, current, SOC) combined with a Dual-Rate Correction Model, which aligns high-rate voltage responses to a reference low-rate curve using SOC-Region Adaptive Correction (SRAC). Without any disassembly, the method estimates Full Charge Capacity (FCC) and internal resistance profiles. Experiments on 8-module packs extracted from commercial EV trucks (2 years, ~10,000 km) showed that FCC estimation error was within ±5% across the SOC range. Compared to the conventional 14 hours/module process, our method reduced total pack screening time to under 6 hours, achieving approximately 40× speed improvement.The proposed approach enables practical mid-SOC range evaluation (20–80%), supports ΔQ/dQdV analysis, and offers extensibility to automated production lines and anomaly detection systems. This work provides a scalable solution for second-life LIB deployment.