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METHOD AND SYSTEM FOR ESTIMATING SOC OF POWER BATTERY ON THE BASIS OF DYNAMIC PARAMETERS

机译:基于动态参数估算动力电池SOC的方法和系统

摘要

Provided are a method and system for estimating SOC of a power battery on the basis of dynamic parameters. The method comprises the following steps: performing a discharging-standing experiment on the battery to obtain an OCV-SOC characteristic curve of the battery at different temperatures, and performing fitting to obtain an OCV-SOC relationship expression; performing a pulse discharging-standing experiment on the battery with a constant current and recording the voltage response during the experiment, and identifying, by using an offline method, an initial parameter value of a second-order RC equivalent circuit model of the battery according to an obtained voltage response curve; performing dynamic parameter identification on the second-order RC equivalent circuit model by using a recursive least-squares method containing a forgetting factor; and performing online estimation of the SOC of the battery by using an EKF algorithm. The estimation method prevents inaccurate SOC initial values and accumulated errors in the ampere-hour integral method, adapts to dynamic changes of battery characteristics, has a high accuracy battery model and high convergence rate, is stable and reliable, improves the accuracy of SOC online estimation, and can be widely used in the field of electric automobiles and energy storage battery management systems.
机译:提供了一种用于基于动态参数来估计动力电池的SOC的方法和系统。该方法包括以下步骤:对电池进行放电静置实验,得到不同温度下电池的OCV-SOC特性曲线;进行拟合,得到OCV-SOC关系式。在恒流下对电池进行脉冲放电直立实验,记录实验过程中的电压响应,并通过离线方法确定电池的二阶RC等效电路模型的初始参数值。获得的电压响应曲线;采用包含遗忘因子的递推最小二乘法对二阶RC等效电路模型进行动态参数识别;并通过EKF算法在线估计电池的SOC。该估计方法避免了安培小时积分法中SOC初始值和累积误差的不准确,适应电池特性的动态变化,具有高精度的电池模型和较高的收敛速度,稳定可靠,提高了SOC在线估计的准确性,可广泛用于电动汽车和储能电池管理系统领域。

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