基于卡尔曼滤波的电力负荷预测算法，针对预测效果不佳，提出了增加改进因子，以提高算法的精度-Power load forecasting algorithm Kalman filter, the prediction results are poor, improvement factor proposed increase, to improve the accuracy of the algorithm

容积卡尔曼滤波测量方程基于统计数据，利用蒙特卡罗方法抽取私家电动汽车一次出行里程数，根据电池充电特性及车辆行驶习惯获得电动汽车充电的起始荷电状态、充电功率和起始充电时间，建立了一个较为精确的预测无线充电私家电动汽车充电负荷的数学模型，(The volume Calman filter measurement equation is based on the statistical data, using Monte Carlo method to extract the first trip m

用容积卡尔曼滤波进行一天时段内的充电负荷预测。(Capacity Kalman filtering is used for charging load forecasting during the day.)

用容积卡尔曼滤波的方法，对电动汽车无线充电的负荷进行预测。(The load of the wireless charging of electric vehicles is forecasted by volume Calman filtering.)