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- W4313193750 abstract "In a battery management system (BMS), cell balancing is an essential function to improve the performance and safe operation of batteries. In the literature, the performance of various cell balancing techniques has been analyzed by assuming ideal circuit parameters. In this paper, model-based quantitative analysis of a capacitive active cell balancing technique with static and dynamic parameters has been presented. A mean current modeling approach is employed to describe energy transfers between battery cells for long charge/discharge operations. The expression of mean current of cell balancing architecture is derived by considering the actual circuit parameters and validated with the simulation results. Moreover, the Kalman filter is designed to estimate the state of charge (SoC), as the efficacy of any balancing architecture mainly relies on the accurate estimation of SoC. The impact of circuit parameters on the performance of the active cell balancing technique has been investigated by performing a detailed sensitivity analysis. The results of sensitivity analysis show that the actual circuit parameters have a significant impact on the efficiency and balancing time of each technique. The efficacy of SoC estimator in cell balancing architecture is also discussed in detail." @default.
- W4313193750 created "2023-01-06" @default.
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- W4313193750 date "2022-08-23" @default.
- W4313193750 modified "2023-10-16" @default.
- W4313193750 title "Model-Based Quantitative Analysis of a Capacitive Cell Balancing Technique using SoC Estimator" @default.
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- W4313193750 doi "https://doi.org/10.1109/ccta49430.2022.9966110" @default.
- W4313193750 hasPublicationYear "2022" @default.
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