基于Kalman算法的软测量技术在电池容量检测中的应用

Application Soft-sensing Technique Based on Kalman Algorithm for Battery Capacity Detection

针对如何在线准确检测实际工作中发射车车载电池容量，提出了一种基于Kalman算法的软测量方法。首先，建立蓄电池数学模型，选择可测、易测的辅助变量，利用Kalman算法建立软测量模型；然后，使用试验数据，通过参数辨识求解软测量模型；最后，利用Matlab软件对该模型进行仿真以及现场试验。结果表明：采用Kalman算法的软测量技术减少了电池应用过程中的电流累积误差，提高了电池容量的检测精度。

In order to accurately detect the practical work capacity of battery for the emission car, a kind of Kalman algorithm based on soft-sensing method is put forward. First of all, the battery mathematical model is established, then, the soft-sensing model is built with selecting measurable, easy measurement auxiliary variables and Kalman algorithm; and then, the soft-sensing model is attained with historical test data and the parameter identification method. Finally, the model is simulated by the Matlab software and tested field. The results show that soft-sensing technique with Kalman algorithm reduces the current cumulative error of battery in the process of application, and improves the battery capacity detection accuracy.