基于多信息融合的车辆状态参数估计

State Estimation of Vehicle Based on Information Fusion

如何获得不同道路条件下的车辆行驶状态,是底盘一体化集成控制系统设计中首先要解决的问题。针对汽车实际行驶过程中,外界干扰及测量条件等因素的影响使汽车行驶状态的关键参数很难通过车载传感器直接获得,提出了采用多信息融合的车辆状态参数估计算法。建立了15自由度车辆模型和车辆多状态参数估计的状态方程;利用多信息融合理论采用双重扩展卡尔曼滤波方法实现了车辆状态参数的实时估计。估计算法与CarSim仿真结果对比显示,信息融合方法具有较高的估计精度,为实车状态参数估计算法研究提供了理论指导。

Vehicle state estimation for VDC system was studied. A 15 DOF vehicle model was built. The method of double extended Caiman filter was established for the vehicle real time stata estimation using multi information fu- sion theory. The simulated results of the vehicle dynamics simulation platform show that the accuracy is improved greatly using the vehicle state estimation method. The method provides a reference with the vehicle state estimation for the vehicle state parameters estimation.