摘要
对电池剩余电量的在线监控可以有效的维护电池的使用寿命,电池相对脆弱,如果充电时间不佳或者工作环境过高,都会对电池的可观察寿命参数产生影响。传统的监控方法进行电池剩余电量的监控时,受到这种参数波动的影响,导致对电池剩余电量的计算有所偏差,存在监控误差大的问题。提出基于改进电量累积法的电池剩余电量的监控方法。将电池剩余电量的监控数据信息进行了分类,利用电量累积法原理表述电池剩余电量数据信息间的递进关系,在利用卡尔曼滤波算法建立电池剩余电量的非线性卡尔曼滤波状态方程和观测方程,再将电池消耗的电能量作为卡尔曼滤波状态变量,电压作为对电池剩余电量的观测信号值,求出当前时刻的电池剩余电能量在线估计值,有效的消除在电池剩余电量监测过程中产生的累积误差,完成对电池剩余电量的监控。仿真结果证明,改进电量累积法的电池剩余电量的监控方法在检测精度和可靠度有明显提高。
A monitoring method of remaining battery power based on the improved energy accumulation approach is proposed. The monitoring data information of remaining battery power is classified. The principle of energy accumulation approach is used to describe the progressive relationship between the data information of remaining battery power. Based on Kalman filtering algorithm,the nonlinear Kalman state equation and observation equation of the remaining battery power are established. Then the consumed electrical energy of battery is as the state variable of Kalman filtering and the voltage is as observed signal value of the remaining battery power,the online estimated value of the residual electric energy of battery at present can be solved,which can effectively eliminate the cumulative error in the monitoring process of remaining battery power,and the monitoring of remaining battery power is completed. The simulation results show that the detection accuracy and reliability of the proposed monitoring method are significantly enhanced.
出处
《计算机仿真》
CSCD
北大核心
2016年第8期101-104,共4页
Computer Simulation
关键词
剩余电量
卡尔曼滤波
电量监控
Remaining power
Kalman filtering
Power monitoring
