基于扩展Kalman滤波技术汽车状态参数的软测量

Soft-measurement for Vehicle State Parameters Based on Extended Kalman Filtering Technology

提出利用扩展Kalman滤波理论对车辆质心侧偏角与横摆角速度状态变量进行间接测量的新方法。研究了卡尔曼滤波理论及其算法的具体流程,建立了基于GIM轮胎模型的整车2自由度动力学观测器模型。与高精度的整车动力学模型仿真对比,结果表明:借助车辆易测量的纵向、横向加速度等信息,结合扩展Kalman滤波技术,对车辆控制系统所需的状态变量进行实时估计,是一种精度高、成本低的有效方法,对于汽车主动安全控制系统在中低档车辆上的推广使用有重要的意义。

A new method using the extended Kalman filter theory to measure indirectly the sideslip angle and yaw rate of vehicle was proposed. The Kalman filter theory and algorithms was studied,and a 2-degree of freedom dynamics observer model of vehicle was established based on the GIM tire model. By contrasting with high-precision vehicle model,the simulation results showed that the estimation method,which measure the state variables required by control system of vehicle with longitudinal and lateral acceleration,was a kind of high precision and low cost technology. It has great significance to promote use of active safety system in the middle and low cars.