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

机译:使用Sigma-point Kalman滤波器估算VRLA电池的状态和参数

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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.
机译:本文介绍了阀控式铅酸蓄电池(VRLA)的混合电气模型及其在Matlab / Simulink环境中的应用。根据电信电池组的充电/放电测试特性,推导出混合动力模型的所有参数。在完成混合电模型的充电/放电模拟并与电池组的实际测试进行比较之后,使用Sigma-point Kalman滤波器(SPKF)对模型状态和参数进行联合估计。进行的联合估计的结果与模型仿真相对应,并且表明SPKF算法对于模型状态和参数的估计是好的。在验证了混合电模型并验证了SPKF算法之后,使用无味卡尔曼滤波器(UKF)方法对VRLA电池组的电池状态和参数进行联合估计,以进行充电/放电测试。

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