State of charge estimation by using extended Kalman filter based on improved open circuit voltage model

Maamar Souaihia, B. Belmadani, R. Taleb, K. Tounsi
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Abstract

This paper focuses on the state of charge estimation (SOC) for battery Li-ion. By modeling a battery based on the equivalent circuit model, the extended Kalman filter approach can be applied to estimate the battery SOC. An electrical battery model is developed in Matlab, Where the structure of the model is detailed by equations and blocks. The battery model has been validated from the experiment results. The comparison shows a good agreement in predicting the voltage, SOC estimation and the model performs better in SOC estimation.
基于改进开路电压模型的扩展卡尔曼滤波电荷状态估计
本文主要研究锂离子电池的荷电状态估计(SOC)问题。基于等效电路模型对电池进行建模,将扩展卡尔曼滤波方法应用于电池荷电状态的估计。在Matlab中建立了一个蓄电池模型,并用方程和模块详细说明了模型的结构。实验结果验证了该电池模型的正确性。结果表明,该模型在电压预测和荷电状态估计上有较好的一致性,且在荷电状态估计上有较好的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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