公交客车纵向车速估算研究

Research on the Estimation of Longitudinal Velocity of Bus

公交客车在ABS工况下轮胎产生较大的滑移,这时纵向车速和轮速相差较大,不能通过轮速来估算车速。为了研究公交客车纵向车速估算问题,文中先建立七自由度整车模型和综合工况下的轮胎模型;然后引入CKF(容积卡尔曼滤波)算法,结合上述整车模型和轮胎模型,推导出CKF算法的系统状态方程和测量方程;最后在MATLAB/SIMULINK中建立CKF算法和系统模型,在TruckSim中设置仿真工况并对真实车辆进行模拟,然后通过MATLAB/SIMULINK和TruckSim联合仿真进行验证,仿真结果表明:CKF算法估算的车速与TruckSim整车模型中计算的车速基本保持一致,从而说明公交客车的纵向车速估算采用CKF算法是有效的。

The tires wil produce a large slip when the bus is in the condition of ABS.The difference of the longitudinal vehicle velocity and wheel speed is large ,so we can not use the wheel speed to estimate the vehicle velocity. In order to study the estimation of the longitudinal vehicle velocity of the bus, the seven-degree-of-freedom vehicle model and the tire model in the comprehensive condition are established firstly. Then, the CKF （Cubature Kalman Filter） algorithm is introduced. Combined with the vehicle model and the tire model, the system state equation and the measurement equation of the CKF algorithm are derived. Finally, the CKF algorithm and the system model are established in MATLAB/SIMULINK. The simulation conditions and the simulation of the real vehicle are carried out in TruckSim. The co-simulation results of MATLAB/ SIMULINK and TruckSim show that the velocity estimated by CKF algorithm is consistent with the velocity from TruckSim model, which indicates that the CKF algorithm is valid for the longitudinal vehicle velocity estimation.