基于卡尔曼滤波算法的车身高度观测
Body height observation based on Kalman filter algorithm
鲍光锐 1郑敏毅 1张农 2钟伟民1
作者信息
- 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
- 折叠
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.
Abstract
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/SimulinkKey words
Kalman filter/height observation/Simulink引用本文复制引用
基金项目
国家自然科学基金面上项目(52272392)
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据