基于扩展卡尔曼滤波法的矿用可移动救生舱蓄电池荷电状态估计

State of charge estimation of battery in mine-used movable lifesaving cabin based on extended Kalman filtering method

针对基于安时计量法的矿用可移动救生舱蓄电池荷电状态SOC估计在环境温度或放电电流波动较大的情况下精度较低的问题,提出了一种基于扩展卡尔曼滤波法的矿用可移动救生舱蓄电池SOC估计方法。该方法在安时计量法的基础上,把影响蓄电池SOC估计的环境温度和放电电流因素作为蓄电池系统的噪声,采用扩展卡尔曼滤波法的优化估计递推算法对蓄电池SOC进行实时滤波与估计,从而提高了蓄电池SOC的估计精度。实验结果表明,该方法的蓄电池SOC估计结果与实测值基本一致,可用于矿用可移动救生舱蓄电池管理系统中。

In view of problem of low precision in SOC estimation of battery in mine-used movable lifesaving cabin based on ampere hour method under condition of higher fluctuation of environment temperature or discharge current,the paper proposed a SOC estimation method of battery in mine-used movable lifesaving cabin based on extended Kalman filtering method.The method is basis on ampere hour method,takes factors of environment temperature and discharge current influencing estimation of SOC of battery as noises of battery system and uses optimal estimation recursive algorithm of extended Kalman filtering method to make real-time filtering and estimation for SOC of battery,which can improve estimation precision of SOC of battery.The experiment result showed that estimation result of SOC of battery used by the method is consistent with measured values and the method can applied to battery management system of mine-used movable lifesaving cabin.