基于轮胎侧偏刚度变化率的车辆质心侧偏角融合估计算法

Fusion Estimation Algorithm of Vehicle Sideslip Angle Based on Changing Rate of Tire Cornering Stiffness

针对车辆在高速紧急避让工况下质心侧偏角难以直接测量的问题,提出一种基于轮胎侧偏刚度变化率的质心侧偏角融合估计算法。在车辆二自由度动力学模型的基础上,提出一种轮胎侧偏刚度估计方法,构建基于改进扩展卡尔曼滤波的质心侧偏角估计算法,根据质心侧偏角和车辆纵向、侧向加速度的关系,构建基于积分法的质心侧偏角估计算法;结合两种估计算法的特点,采用轮胎侧偏刚度的一阶微分表征车辆的非线性程度,设计了一种适用于不同车辆动态特性及路面条件的融合估计算法。Carsim/Simulink联合仿真结果表明,该融合估计算法在不同的车辆动态特性和不同路面条件下具有良好的估计精度和实时性,对传感器信号的噪声、误差鲁棒性强。

In order to solve the problem that it is difficult to directly measure the vehicle sideslip angle under the condition of obstacle avoidance at high speeds,a fusion estimation algorithm of vehicle sideslip angle based on changing rate of tire cornering stiffness was proposed.On the basis of the 2-DOF vehicle dynamic model,a tire cornering stiffness estimation method was proposed,and an estimation algorithm of vehicle sideslip angle based on improved extended Kalman filter(EKF)was constructed.According to the relationship between the vehicle sideslip angle and vehicle longitudinal and lateral accelerations,an integral method was proposed to estimate the vehicle sideslip angle.Then combined with the characteristics of the two estimation algorithms,the first order differential of tire cornering stiffness was used to characterize the nonlinear degree of vehicles,and a fusion estimation algorithm for multi-vehicle dynamic characteristics and multi-road conditions was designed.The results based on the Carsim/Simulink co-simulation platform show that the fusion estimation algorithm has excellent estimation accuracy and real-time performance under various vehicle dynamic characteristics and road conditions,and it is also robust to noise and error of sensor signals.