摘要
多轴重型特种车辆具有载重大、质心高、速度快的特点,在高机动行驶条件下存在发生操纵失稳的可能性。质心侧偏角和横摆角速度是衡量车辆操稳性的关键判据,如果直接通过车载传感器测量存在测量困难、成本昂贵和长时误差等问题,因此开展了对五轴重型车辆的状态估计研究。基于Matlab/Simulink搭建了五轴特种车辆的13自由度动力学模型,利用行驶状态监测系统进行实车试验,验证模型的精确性,为估计模型提供理论依据及验证仿真平台。建立非线性三自由度车辆模型,基于无迹卡尔曼滤波算法,设计关于横摆角速度、质心侧偏角、纵向速度的状态估计器。以13自由度模型为仿真平台分别进行角阶跃输入、脉冲输入及正弦输入工况的验证。仿真结果证明,基于非线性三自由度车辆模型的状态估计器可实现对纵向速度、横摆角速度和质心侧偏角参数的动态估计。
Multi-axle heavy special vehicle has characteristics of heavy load, high mass center and fast speed, they may cause handling instability under high maneuver driving conditions. Sideslip angle of mass center and yaw angular speed were key criteria to measure vehicle handling stability. In practice, when vehicle was directly measured with on-board sensors, there were problems of measurement difficulty, high cost and long-term error. Here, studying state estimation of 5-axle heavy vehicle was performed. Firstly, a 13-DOF dynamic model for 5-axle special vehicle was built based on the software Matlab/Simulink. Actual vehicle tests were conducted using the driving state monitoring system to verify the correctness of the model, and provide a theoretical basis and a verification simulation platform for estimation of the model. Then, a nonlinear 3-DOF vehicle model was established. Based on the unscented Kalman filter algorithm, state estimators of yaw angular speed, sideslip angle of mass center and longitudinal speed were designed. Finally, the 13-DOF model was taken as the simulation platform for verification under working conditions of angular step input, pulse input and sinusoidal input, respectively. Simulation results showed that the state estimator based on the nonlinear 3-DOF vehicle model can realize dynamic estimation for parameters of longitudinal speed, yaw angular speed and sideslip angle of mass center.
作者
于传强
舒洪斌
刘志浩
陈渐伟
高杨
YU Chuanqiang;SHU Hongbin;LIU Zhihao;CHEN Jianwei;GAO Yang(College of Missile Engineering,Rocket Force Engineering University,Xi’an 710025,China;Military Representative Office of Rocket Force Equipment Department in Changzhi District,Changzhi 046000,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2023年第5期269-278,共10页
Journal of Vibration and Shock
基金
国家自然科学基金(51905541)
陕西省自然科学基础研究计划(2020JQ487)。
关键词
五轴重型车辆
动力学模型
实车验证
无迹卡尔曼滤波(UKF)
状态估计
5-axle heavy vehicle
dynamic model
actual vehicle verification
unscented Kalman filter(UKF)
Simulink
state estimation
