基于自适应Kalman滤波的VMAS车速信号处理

摘要

This paper uses numerical simulation examples to verify the filtering effects of the Kalman filtering de-noising method by comparing it with the traditional FIR filtering method.The state space model of speed signal filtering during the vehicle mass analysis system（VMAS） tests is established;the Kalman filtering method is used to test the constant speed mode and the acceleration mode of the VMAS;the test results prove the effectiveness of the speed signal processing method.The paper also develops a new adaptive Kalman filtering algorithm for the speed signal processing of the VMAS through using the test data and applies the algorithm to filtering its full-condition test data.The comparison of the adaptive Kalman filtering algorithm with the conventional Kalman filtering algorithm shows that the new adaptive Kalman filtering algorithm has higher estimation accuracy,stronger adaptability for the speed signal processing during VMAS tests.%用仿真算例研究了卡尔曼滤波方法的滤波效果,与传统的FIR滤波法进行了比较,证明了卡尔曼滤波法的有效性。建立了VMAS测试中速度滤波的状态空间模型。并基于这一模型,用卡尔曼滤波方法进行了等速和加速工况的实测信号验证。提出了一种用于VMAS速度信号处理的自适应Kalman滤波算法。运用该算法对实车测试的全工况数据进行了滤波处理,通过与普通Kal-man滤波进行比较,证明该算法在VMAS测试的信号处理中具有适应性强、估计精度高的特点。