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Experimental Research on the LiNi_xCo_yMn_zO_2 Lithium-ion Battery Characteristics for Model Modification of SOC Estimation

机译:LiNi_xCo_yMn_zO_2锂离子电池特性用于SOC估计模型修正的实验研究

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摘要

The Kalman Filter (KF) known as an optimum adaptive algorithm based on recursive estimation, has been widely used to estimate the State Of Charge (SOC) of the lithium-ion batteries. To improve the performance of SOC estimation, the parameters of battery model in the KF method should be chosen correctly. Nevertheless, the battery parameters, such as the OCV-SOC, capacity and resistance are significantly depended on the battery SOC, temperature, current and ageing. In this study, these dependencies and their variation over the temperature, current and ageing are investigated on a Samsung ICR18650-22P-typed lithium-ion battery with LiNi_xCo_yMn_zO_2 cathode which offers guidance to model modification of SOC estimation. The experimental results show that the OCV-SOC relationship are strong consistent under the conditions of 0~60℃ but it varies when the temperature remains below zero degrees Celsius. The capacity varies considerably with the temperature and cycles and slightly with the current of below 3C. The Ohmic resistance varies slightly with charge current but considerably with discharge current and SOC. Based on the experimental results, some suggestion for model modification of SOC estimation is put forward.
机译:卡尔曼滤波器(KF)被称为基于递归估计的最佳自适应算法,已被广泛用于估计锂离子电池的荷电状态(SOC)。为了提高SOC估计的性能,应正确选择KF方法中的电池模型参数。但是,电池参数(例如OCV-SOC,容量和电阻)在很大程度上取决于电池SOC,温度,电流和老化。在这项研究中,在具有LiNi_xCo_yMn_zO_2阴极的Samsung ICR18650-22P型锂离子电池上研究了这些依赖性及其随温度,电流和老化的变化,这为SOC估计的模型修改提供了指导。实验结果表明,在0〜60℃条件下,OCV-SOC关系具有很强的一致性,但当温度保持在零摄氏度以下时,OCV-SOC关系会发生变化。容量随温度和周期而变化很大,而低于3C的电流则略有变化。欧姆电阻随充电电流而略有变化,但随放电电流和SOC则变化很大。在实验结果的基础上,提出了SOC估计模型修正的一些建议。

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