Amirkabir University of Technology AUT Journal of Electrical Engineering 2588-2910 Articles in Press 2026 06 15 New Approach to Assembling Used 18650 Cells by the DBSCAN Clustering Algorithm 6065 10.22060/eej.2026.24892.5788 EN Mohamed Redha Rezoug Department of Electrical Engineering, Faculty of Technology, Kasdi Merbah University – Ouargla 30000, Algeria 0000-0003-1849-8989 Laid Khettache Department of Electrical Engineering, Faculty of Technology, Kasdi Merbah University – Ouargla 30000, Algeria 0000-0002-3388-3669 Abdeslam Benmakhlouf Department of Electrical Engineering, Faculty of Technology, Kasdi Merbah University – Ouargla 30000, Algeria 0000-0003-0849-7229 Djalal Djarah Department of Electrical Engineering, Faculty of Technology, Kasdi Merbah University – Ouargla 30000, Algeria 0000-0002-2480-9731 Journal Article 2025 10 17 This study presents a diagnostic and regrouping approach for used 18650 lithium-ion cells using the DBSCAN clustering algorithm. A total of 154 cells were recovered from discarded laptop batteries. After electrical testing (constant-current discharge measuring capacity, voltage, and internal resistance), 120 cells (78%) were identified as healthy and suitable for reuse. The DBSCAN algorithm (eps=0.3, min_samples=10) was applied to cluster these 120 cells based on their electrical characteristics. The algorithm successfully formed three homogeneous clusters of 40 cells each. These clusters were assembled in a 3S40P configuration (three parallel packs of 40 cells connected in series) to form a second-life battery of approximately 81 Ah capacity at 10.9 V. Comparative analysis shows that DBSCAN outperforms K-means and hierarchical clustering for this application, achieving a silhouette coefficient of 0.62 versus 0.48 for K-means. The proposed method achieves a 78% cell recovery rate, demonstrating its effectiveness for battery recycling and second-life applications. https://eej.aut.ac.ir/article_6065_dfd786998e082758be12670d856df755.pdf