The State of Charge estimation employing empirical parameters measurements for various temperatures

Jonghoon Kim, Seongjun Lee, Bohyung Cho
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引用次数: 27

Abstract

The State of charge (SOC) estimation algorithm uses the model parameter, which includes capacity, open circuit voltage (OCV), resistance and capacitance. These model parameter values are subject to be changed at varying temperatures[1–4]. In order to estimate SOC for temperature variation, it is indispensable to include the temperature effect on battery's performance. In this paper, the state of charge estimation employing empirical parameters measurements is introduced for SOC estimation for various temperatures. The internal parameters are measured on Li-Ion batteries from 10°C through 50°C at an interval of 10°C. Especially, the modified parameters are applied to estimate SOC at below room temperature and low SOC. The measured results are incorporated in the extend kalman filter (EKF) algorithm[5,6] and verified by comparison of Ah-counting and EKF result. The estimation and the results are shown to be under 3%.
利用经验参数测量不同温度下的电荷状态估计
荷电状态(SOC)估计算法使用模型参数,包括容量、开路电压(OCV)、电阻和电容。这些模型参数值在不同的温度下会发生变化[1-4]。为了估算温度变化下的荷电状态,必须考虑温度对电池性能的影响。本文介绍了基于经验参数测量的荷电状态估计方法在不同温度下的荷电状态估计。内部参数在10°C至50°C的锂离子电池上以10°C的间隔进行测量。特别地,修正后的参数适用于低于室温和低荷电状态下的荷电状态估计。将测量结果纳入扩展卡尔曼滤波(EKF)算法[5,6],并通过ah计数和EKF结果的比较进行验证。估计和结果显示在3%以下。
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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