SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF

Honggang Du, Guangchen Liu, Jianwei Zhang, G. Tian, Shengtie Wang
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引用次数: 1

Abstract

Accurate estimation of the state of charge (SOC) of Lithium-ion batteries is the critical technology for developing Lithium-ion batteries. Aiming at the problem that the noise covariance of the UKF is fixed, an adaptive UKF algorithm is proposed in this paper. The adaptive UKF algorithm can estimate and correct the noise characteristics of the system in real-time, and suppress the possible filter divergence and improve the estimation accuracy of the SOC. By analyzing the simulation results of constant discharge and pulsed variable current pulse discharge, it is proved that the filtering effect of adaptive UKF is better and the accuracy is higher.
基于自适应UKF的锂离子电池荷电状态估计
准确估算锂离子电池的荷电状态是锂离子电池发展的关键技术。针对UKF噪声协方差固定的问题,提出了一种自适应UKF算法。自适应UKF算法能够实时估计和校正系统的噪声特性,抑制可能出现的滤波发散,提高SOC的估计精度。通过对恒放电和脉冲变电流脉冲放电的仿真结果分析,证明了自适应UKF滤波效果较好,精度较高。
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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