基于平方根无迹卡尔曼滤波算法的电动汽车质心侧偏角估计

摘要

The side‐slip angle of electric vehicle can not be directly and conveniently measured by using sensors .To solve this problem ,a Square‐Root Unscented Kalman Filter (SR‐UKF) algorithm was proposed to estimate the side‐slip angle .First , the lateral dynamics model of the vehicle and the nonlinear dynamics model of the tire were established .Then ,based on the models and the estimated side‐slip angle , the cornering stiffness of the tire was estimated by using least square method . Experiments were carried out to verify the effectiveness of the algorithm in estimating the side‐slip angle of electric vehicle .Results show that the proposed method has high precision and can provide effective vehicle state information for the design of the stability control system of the vehicle .%针对电动汽车质心侧偏角不便使用传感器直接测量的问题,提出采用平方根无迹卡尔曼滤波(SR‐UKF)算法来估计电动汽车质心侧偏角.基于建立的车辆侧向动力学模型、非线性轮胎动力学模型以及估计得到的质心侧偏角,使用最小二乘法对轮胎侧偏刚度进行估计,得到轮胎侧偏刚度信息.最后,通过试验验证了基于SR‐UKF的电动汽车质心侧偏角估计算法具有较高的精度,能够为后续车辆稳定性控制系统的设计提供有效的车辆状态信息.