Utilizing Ensemble Models Under Various Discharge Conditions for Static Capacity Estimation to Promote the Reuse of Retired EV Batteries

The rapid proliferation of electric vehicles has posed significant challenges regarding the disposal of end-of-life lithium-ion batteries. Effective re-use, remanufacturing, and recycling of these batteries are essential for sustainable resource management and reducing environmental impact. By enabling circular use of battery materials, these processes can substantially mitigate greenhouse gas emissions, conserve natural resources, and minimize waste generation. However, achieving these sustainable battery life cycles requires accurate and rapid health assessments. Traditional evaluation methods are often time-consuming and costly, limiting their applicability for profitable industrial operations. This study proposes a novel rapid assessment method that utilizes partial discharge data collected over a brief three-minute period to evaluate battery capacity. By applying an ensemble technique, the proposed approach maintains high accuracy with a mean RMSE of 0.64% while significantly reducing diagnostic time. Cost analysis reveals that this method achieves approximately 60-fold of time savings and 58-fold of cost reduction compared to a conventional technique. This rapid diagnostic approach provides substantially practical benefits to the processes of battery reuse, remanufacturing, and recycling. Quick and reliable assessments enable the effective sorting of batteries for reuse in other applications such as energy storage systems and low-power applications, as well as for remanufacturing through modular reconfiguration. The proposed methodology thus offers a practical and efficient solution to support the development of a sustainable circular economy for lithium-ion batteries, contributing to the broader goals of green technology and environmental protection.