Estimation of VRLA battery states and parameters using Sigma-point Kalman filter

Goran Kujundžić, M. Vašak, J. Matuško
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引用次数: 14

Abstract

This paper describes a hybrid electrical model of valve-regulated lead-acid battery (VRLA) and its application in Matlab/Simulink environment. Based on the charge/discharge test characteristics of the telecommunication battery stack, all parameters of the hybrid electrical models are derived. After implementing the charge/discharge simulations of hybrid electrical model and comparisons with actual tests of battery stack, joint estimation of model states and parameters is carried out using Sigma-point Kalman filter (SPKF). Results of performed joint estimation correspond to model simulations and it is shown that the SPKF algorithm is good for estimation of model states and parameters. After validation of the hybrid electrical model and validation of SPKF algorithm, joint estimation of battery states and parameters is performed to charge/discharge test of VRLA battery stack using Unscented Kalman Filter (UKF) method.
用西格玛点卡尔曼滤波估计VRLA电池状态和参数
本文介绍了阀控铅酸蓄电池的混合电气模型及其在Matlab/Simulink环境下的应用。根据通信电池堆的充放电试验特点,推导了混合电模型的各项参数。通过对混合动力模型进行充放电仿真,并与电池组实际试验结果进行比较,利用西格玛点卡尔曼滤波(SPKF)对模型状态和参数进行联合估计。联合估计结果与模型仿真结果相吻合,表明SPKF算法对模型状态和参数的估计效果较好。在对混合电模型和SPKF算法进行验证后,采用Unscented卡尔曼滤波(UKF)方法对VRLA电池组的充放电测试进行电池状态和参数的联合估计。
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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