SOC inconsistency estimation using sensor fusion method based on the dual extended Kalman filter neglecting the cell-to-cell's aging condition

Most inconsistency estimation approaches depend on historical inhomogeneity sensor data that might not be practicable in real-time application because the battery voltage dynamics are non-linear characteristics according to the various internal and external condition such as cell-to-cell's configuration, initial state, etc. To overcome this problem, the state ob-server requires the integrated approaches that consider minimi-zation method considering degradation process and measured data. In this paper, the iteration model with various parameters that affect the over-discharge to cell in the battery, and the cell-to-cell's parameters is identified using adaptive model and sen-sor fusion method for analyzing the influence of failure evaluation. To eliminate the effect of aging condition and reflect the uncertainty of battery voltage signal, the self-adaptive model is utilized to estimate the cell-to-cell SOC inconsistency. The theo-retical analysis is validated using experimental results in aspect of the feasibility and advantages of the proposed method