| Title |
Model-based Analysis of Cell-to-Cell Imbalance Characteristic Parameters in the Battery Pack for Fault Diagnosis and Over-discharge Prognosis |
| Authors |
Jinhyeong Park ; Jaewon Kim ; Miyoung Lee ; Byoung-Choul Kim ; Sung-Chul Jung ; Jonghoon Kim |
| DOI |
https://doi.org/10.6113/TKPE.2021.26.6.381 |
| Keywords |
Adaptive control algorithm; BMS (Battery Management System); EECM (Electrical Equivalent Circuit Model); Fault prognosis |
| Abstract |
Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis. |