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State-of-charge And Capacity Estimation Of Lithium-ion Battery Using A New Open-circuit Voltage Versus State-of-charge

机译:使用新的开路电压与充电状态的锂离子电池的充电状态和容量估算

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摘要

Open-circuit voltage (OCV) is widely used to estimate the state-of-charge (SoC) in many SoC estimation algorithms. However, the relationship between the OCV and SoC cannot be exactly same for all batteries. Because the conventional OCV-SoC differs among batteries, there is a problem in that the relationship of the OCV-SoC should be measured to estimate accurately the SoC. Therefore, a modified OCV-SoC relationship based on the conventional OCV-SoC is proposed. Problems resulting from the defects of the extended Kalman filter (EKF) can be avoided by preventing the relationship from varying. Also, in order to improve the performance of the algorithm, measurement noise models of the Kalman filter are applied. Thus, the measurement noise models allow the Kalman filter to overcome defects from the simplified battery modelling and to separate the sequence for estimation of the state and weight filter. The SoC and the capacity of a lithium-ion battery are estimated using the dual EKF with the proposed method.
机译:在许多SoC估计算法中,开路电压(OCV)被广泛用于估计充电状态(SoC)。但是,并非所有电池的OCV和SoC之间的关系都完全相同。由于传统的OCV-SoC在电池之间存在差异,因此存在一个问题,即应测量OCV-SoC的关系以准确估计SoC。因此,提出了一种基于传统OCV-SoC的改进的OCV-SoC关系。通过防止关系变化,可以避免由扩展卡尔曼滤波器(EKF)的缺陷引起的问题。另外,为了改善算法的性能,应用了卡尔曼滤波器的测量噪声模型。因此,测量噪声模型允许卡尔曼滤波器克服简化电池建模带来的缺陷,并分离用于估计状态和权重滤波器的顺序。使用提出的方法使用双EKF估计SoC和锂离子电池的容量。

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