| Title |
Z-score Based Abnormal Detection for Stable Operation of the Series/Parallel-cell Configured Battery Pack |
| Authors |
Deokhun Kang ; Pyeong-Yeon Lee ; Deokhan Kim ; Seung-Keun Kim ; Jonghoon Kim |
| DOI |
https://doi.org/10.6113/TKPE.2021.26.6.390 |
| Keywords |
BMS (Battery Management System); Z-score; Statistical method; Abnormal detection |
| Abstract |
Lithium-ion batteries have been designed and used as battery packs with series and parallel combinations that are suitable for use. However, due to its internal electrochemical properties, producing the battery’s condition at the same value is impossible for individual cells. In addition, the management of characteristic deviations between individual cells is essential for the safe and efficient use of batteries as aging progresses with the use of batteries. In this work, we propose a method to manage deviation properties and detect abnormal behavior in the configuration of a combined battery pack of these multiple battery cells. The proposed method can separate and detect probabilistic low-frequency information according to statistical information based on Z-score. The verification of the proposed algorithm was validated using experimental results from 10S3P battery packs, and the implemented algorithm based on Z-score was validated as a way to effectively manage multiple individual cell information. |