The Analysis of Modeling of Dual Kalman Filter in Lithium Battery SOC Estimates

Jian Long Huang; Zhong Feng Wang; Kun Ya Guo; Xiao Tian Wang; Li Gang Li; Zhe Zhu Huang

doi:10.4028/www.scientific.net/AMM.513-517.4294

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517The Analysis of Modeling of Dual Kalman Filter in...

The Analysis of Modeling of Dual Kalman Filter in Lithium Battery SOC Estimates

Abstract:

In order to online estimate the state of charge (SOC) of lithium-ion battery pack in this paper. This article establishes a dual Kalman filter (DEKF) algorithms for it. We establish a battery model of state space expression based on Thevenin battery model and Kalman filter algorithms. We use least square method and DEKF algorithms to identify the parameters of battery model in order to improve the accuracy of battery model. It can make battery model reflect true state of internal battery well. It introduces the principle which is dual Kalman filter algorithm online estimate the state of charge. Finally, it verifies DEKF algorithm has better convergence and robustness which can effectively resolve the problems of initial estimates error and cumulative error issue.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

4294-4297

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.4294

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Online since:

February 2014

Authors:

Jian Long Huang*, Zhong Feng Wang, Kun Ya Guo, Xiao Tian Wang, Li Gang Li, Zhe Zhu Huang

Keywords:

Dual Kalman Filter, Least-Square Method (LSM), Lithium-Ion Battery, State of Charge (SOC)

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References

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