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Identification of the non-linear dynamics and state of charge estimation of a LiFePO 4 battery using constrained unscented Kalman filter

机译:使用约束无味卡尔曼滤波器识别LiFePO 4 电池的非线性动力学和电荷状态估计

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State of charge (SOC) estimation of a LiFePO 4 battery exhibiting significant hysteresis is considered. The dynamics of the battery is modeled as a linear system in conjunction with a non-linear hysteresis block. The linear part is assumed to be of a second order equivalent circuit model along with an open circuit voltage (OCV) source V oc . The circuit model is descretised and the resulting parameters are modeled as a multivariate random walk with a diagonal noise covariance matrix. These parameters are estimated using a Kalman filter. The linear model is then validated using a hybrid pulse power characterisation (HPPC) current profile. The major loop of the non-linear hysteresis relating V oc and SOC is experimentally determined by charging and discharging the battery with low magnitude currents. Using Chebyshev polynomials, a model is fit for the hysteresis curves. Constrained unscented Kalman filter (CUKF) is used for estimating the minor loops of the hysteresis, and the SOC. The SOC estimation is then validated from a full electrochemical model simulation of the battery using COMSOL software.
机译:考虑显示出显着滞后的LiFePO 4电池的充电状态(SOC)估计。电池的动力学建模为线性系统,并带有非线性磁滞模块。线性部分与开路电压(OCV)源V oc一起假定为二阶等效电路模型。减少电路模型,并将得到的参数建模为带有对角噪声协方差矩阵的多元随机游动。这些参数是使用卡尔曼滤波器估算的。然后,使用混合脉冲功率表征(HPPC)电流曲线来验证线性模型。通过以低幅值电流对电池进行充电和放电实验确定了与V oc和SOC相关的非线性磁滞的主回路。使用Chebyshev多项式,模型适用于磁滞曲线。约束无味卡尔曼滤波器(CUKF)用于估计磁滞和SOC的次要环路。然后,使用COMSOL软件从电池的完整电化学模型仿真中验证SOC估算。

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