重型车辆运动状态估计仿真研究

Estimation of Heavy Duty Vehicle Motion State

重型车辆主动安全研究的核心是如何快速获取车辆运行状态、环境等参数,并将这些参数进行综合分析,按照一定的规律对车辆进行控制。车辆运动状态参数有的可以直接通过车载传感器测量得到,有的则不能。通过建立重型车辆的七自由度动力学模型,利用无迹卡尔曼滤波状态估计方法求解重型汽车在双移线试验下的运动状态参数,将获得的结果与同参数下的Trucksim计算结果进行对比,仿真结果表明,该方法能够实现重型车辆运动状态的估计,并且具备较高的估计精度。

How to acquire the vehicle motion status,environment and other parameters quickly and then control the vehicle according to some certain rules which comes from the comprehensive analysis for the parameters is the core of the research on heavy duty truck active safety.Some of the vehicle motion state parameters can be directly measured by on-board sensors,while others cannot.The 7DOF dynamic model is built.Using the Unscented Kalman Filter method solves the motion status under the double lane change test.The simulation results show that the proposed method has higher estimation accruacy.