【摘要】 针对车辆在高速转向工况下易发生失稳的问题，提出一种多状态估计优化模型对车辆运动参数进行估计。首先对车辆与轮胎进行动力学分析，建立车辆模型。由于车辆参数在运动过程中难以直接测量，建立了基于魔术公式轮胎的扩展卡尔曼滤波（extended Kalman filter,EKF）多状态估计优化模型对车辆参数进行估计。最终选用Carsim与MATLAB/Simulink作为联合仿真平台，通过高、低附着路面下的闭环双移线实验开展高速转向下的仿真分析。实验结果表明，车辆在不同工况下能够有效跟踪期望横摆角速度且质心侧偏角均趋近于0。同时，从质心侧偏角相平面可以看出，车辆在极限工况下仍能行驶在稳定区域。更多还原

【Abstract】 Aiming at the problem that vehicles are prone to instability under high-speed steering conditions, a multistate estimation optimization model was proposed to estimate the vehicle motion parameters. The vehicle model was established firstly via dynamics analysis of the vehicle and tires. Due to the difficulty in the direct measurement of the vehicle parameters during the motion process, a multistate estimation optimization model based on extended Kalman filter(EKF) with magic formula tires was established to estimate the vehicle parameters.Carsim and MATLAB/Simulink were finally chosen as the joint simulation platform, and the simulation experiment under high speed steering was carried out through the closed-loop double-shift line experiment under high and low adhesion road surface. The experimental results show that the vehicle can effectively track the desired swing angular velocity under different working conditions and the center of mass lateral deflection angle is close to 0. Meanwhile, the phase plane of the center of mass lateral deflection angle shows that the vehicle can still run in the stable region under the extreme working conditions.更多还原