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Research on optimized SOC estimation algorithm based on extended kalman filter
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DOI：10.3389/fenrg.2022.1027439.png)
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摘要
En 中文
The paper studies the estimation of state of charge (SOC) of batteries. Firstly, the research status of battery management system, battery equivalent model and SOC estimation algorithm is introduced, and the performance of common equivalent circuit model and SOC estimation algorithm in complexity and accuracy is compared and analyzed. On this basis, this paper proposes an extended Kalman filter (EKF) algorithm based on the first-order RC model, and optimizes it by piecewise fitting. The accuracy of the optimized EKF algorithm is greatly improved. Finally, the modeling and simulation are completed through MATLAB/SIMULINK, and the experimental platform is designed and built to test the SOC estimation algorithm based on EKF. The simulation and experimental results verify the accuracy of the estimation algorithm.
Keyword:
state of charge
estimation algorithm
extended kalman filter nomenclature
simulink (RRID:SCR_014744)
matlab (RRID:SCR_001622)
kalman filter
期刊
IF:
2.4
论文数:
1.0K
被引数:
1.4W
机构
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