泰文定理
荷电状态
电池(电)
等效电路
卡尔曼滤波器
电压
可靠性(半导体)
扩展卡尔曼滤波器
功率(物理)
工程类
计算机科学
电子工程
控制理论(社会学)
电气工程
人工智能
物理
控制(管理)
量子力学
作者
Xu Zhu,Shibin Gao,Shunfeng Yang
摘要
Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge (SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteristics of the LiFePO4 battery, and the model parameters are identified by experimental testing. Furthermore, a novel algorithm of SOC online estimation is proposed, which combines the open-circuit voltage method, ampere-hour integration, and Kalman filtering. The simulations and experimental results show that the improved Thevenin equivalent circuit model can enhance the accuracy of SOC estimation. This proposed algorithm could estimate the SOC precisely even with inaccurate initial values and current measurement errors and distinguish the performances between the batteries. The performance of the proposed SOC estimation method when the voltage sensor is unavailable has been investigated and presented as well. From the characteristics mentioned above, this novel approach is able to guarantee the reliability and safety of the batteries.
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