基于卡尔曼滤波算法的车身高度观测  

Body height observation based on Kalman filter algorithm

作　　者：鲍光锐 郑敏毅 张农 钟伟民 BAO Guangrui;ZHENG Minyi;ZHANG Nong;ZHONG Weimin(School of Automotive and Transportation,Hefei University of Technology,Hefei 230009,Anhui,China;Institute of Automobile Engineering Technology,Hefei University of Technology,Hefei 230009,Anhui,China)

机构地区：[1]合肥工业大学汽车与交通工程学院,安徽合肥230009 [2]合肥工业大学汽车工程技术研究院,安徽合肥230009

出　　处：《农业装备与车辆工程》2024年第2期44-48,共5页Agricultural Equipment & Vehicle Engineering

基　　金：国家自然科学基金面上项目(52272392)。

摘　　要：为解决直接使用超声波以及激光雷达测距容易受到路面情况的干扰的问题,提出了一种基于卡尔曼滤波算法。运用MATLAB/Simulink建立整车模型,建立车身高度观测器,从而实现实时且准确地获得车身高度,为车辆控制策略提供准确的车辆质心高度参数。利用仿真模型进行双移线工况和减速带工况的仿真分析,对静止车辆施加随机激励进行了实车实验。仿真和实验结果表明:卡尔曼滤波算法的车身高度观测器可以实时且准确地获得车身高度,具有较好的精确度。Since the direct use of ultrasonic and lidar ranging was easily interfered by road conditions,in order to solve the above contradiction,a Kalman filtering algorithm was proposed.Using MATLAB/Simulink,a vehicle model and a body height observer were established,so as to achieve real-time and accurate acquisition of body height.Accurate vehicle centroid height parameters for vehicle control strategies were provided.The simulation model was used to simulate and analyze the double-line shift condition and speed bump condition,and the random excitation was applied to the stationary vehicle to carry out the real vehicle experiment.Simulation and experimental results showed that the body height observer of Kalman filter algorithm can obtain the body height in real time and accurately,with good accuracy.

关 键 词：卡尔曼滤波 高度观测 SIMULINK 

分 类 号：U463.33[机械工程—车辆工程]