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Battery SOC Estimation Based on LM-ICDKF Algorithm
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DOI：10.1109/ICICTA.2017.13.png)
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Abstract
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In order to estimate the accurate and real-time dynamic battery state of charge (SOC), owing to greater errors of extended Kalman filter (EKF) in estimating SOC, a method has been proposed to estimate the battery SOC based on LMICDKF algorithm. By using the two order RC equivalent circuit model, the MATLAB simulation tools are used to simulate the algorithm, this paper compares LM-ICDKF algorithm with the extended Kalman filter algorithm and the center differential Kalman filter algorithm. From the simulation results, we can indicate that the SOC estimation based on LM-ICDKF has good convergence, and improves the estimation accuracy of SOC.
Keywords:
SOC
MATLAB
LM-ICDKF
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