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• W4310521244 abstract "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" @default.
• W4310521244 created "2022-12-11" @default.
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• W4310521244 date "2022-10-09" @default.
• W4310521244 modified "2023-10-18" @default.
• W4310521244 title "SOC inconsistency estimation using sensor fusion method based on the dual extended Kalman filter neglecting the cell-to-cell's aging condition" @default.
• W4310521244 cites W2007672025 @default.
• W4310521244 doi "https://doi.org/10.1109/ecce50734.2022.9947965" @default.
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