基于无迹卡尔曼滤波软测量技术的汽车行驶状态估计  

Vehicle Driving State Estimation Based on Unscented Kalman Filter Soft Computing Technigue

作　　者：郝亮[1,2] 郭立新 HAO Liang;GUO Li-xin(Automobile&Traffic Engineering College,Liaoning University of Technology,Jinzhou 121001,China;School of Mechanical Engineering&Automation,Northeastern University,Shenyang 110819,China)

机构地区：[1]辽宁工业大学汽车与交通工程学院,锦州121001 [2]东北大学机械工程与自动化学院,沈阳110819

出　　处：《科学技术与工程》2018年第27期79-84,共6页Science Technology and Engineering

基　　金：国家自然科学基金(50875041);新世纪优秀人才支持计划项目(NCET-08-0103);中央高校基本科研业务费专项资金(N110403008);国家自然科学青年基金(51305190);辽宁省教育厅重大科技平台科技项目(JP2016011)资助

摘　　要：为了有效解决电动汽车在行驶过程中的车速、质心侧偏角和横摆角速度等参数低成本测量的问题,采用无迹卡尔曼搭建了软测量算法;该算法充分考虑电动汽车动态行驶状况下非线性的影响因素,同时采用非线性的高速公路研究所动态轮胎模型对轮胎侧向力进行精确估计。通过与Car Sim动力学仿真软件进行联合仿真,对比分析验证所建立的软测量算法能够准确、实时地估计出电动汽车的运动参数。UKF soft computing algorithm is adopted to solve low-cost measurement of electric vehicle dring states parameters including velocity,centroid slip angle and yaw rate and it takes a full account of nonlinear factors of electric vehicle driving condition.Nonlinear highway research institute dynamic tire model can be adapted to accurately estimate tire lateral forces.Finally co-simulation is carried out based on CarSim and MATLAB/simulink.The results prove that soft computing algorithm can accurately and real-time estimate the dynamic vehicle parameters.

关 键 词：电动汽车 低成本测量 无迹卡尔曼滤波 软测量算法 高速公路研究所动态轮胎模型 联合仿真 

分 类 号：U463.42[机械工程—车辆工程] U469.722[交通运输工程—载运工具运用工程]