微网系统中储能电池荷电状态估计方法

State of Charge Estimation of Energy Storage Battery in Micro-grid Systems

蓄电池作为储能设备,其荷电状态(SOC)是整个电池储能系统的重要参数。采用戴维南模型构造了电池数学模型,并建立状态空间方程。模型参数的辨识采用恒流间歇放电实验法求得。计算各参数的初值,拟合各参数与SOC之间的函数关系,结合模型的电气特性建立状态空间方程并利用Matlab仿真出电压数据,对仿真、实验电压数据进行对比,按照无约束非线性优化的方法在两者差值最小时在线搜索出最佳的参数估计。所辨识的参数能够很好地模拟电池性能,误差在1%内。采用扩展卡尔曼估算方法来进行SOC估算,通过实验验证了此估算方法具有很高的估算精度,误差在4%以内。

The battery as an energy storage device, its state of charge （SOC） is an important parameter of the entire battery energy storage system.Thevenin model is used as the battery mathematical model,and the state-space equations are establlshed.The identification msuh of the model parameters uses the constant current intermittent discharge test method.The initial value of each parameter is calculated ,it fits the function relationships between the parameters and the SOC.A set of state-space equations combined with the electrical characteristics of the model are established, and the emulational voltage data are obtained by using Matlab.Compared with the simulation and experimental voltage data, the best parameter estimation according with unconstrained nonlinear optimization methods by the minimum difference between the two kinds of data is searched out.It simulates the battery performance very well to use the identifiable parameters, the error within 1%.Extended Kalman estimation method is used to estimate the SOC ,and it finally verifies this estimation method has a high accuracy of estimation through laboratory, the error within 4%.