汽车运动状态在线测量及预报技术  

On-line Measurement and Prediction Technology for Vehicle Motion State

作　　者：刘军[1] 董晶晶[1] 时枭鹏[1] 何国国[1] 

机构地区：[1]江苏大学汽车与交通工程学院,江苏镇江212013

出　　处：《中国公路学报》2011年第4期114-121,共8页China Journal of Highway and Transport

基　　金：汽车动态模拟国家重点实验室开放基金项目(20071104)

摘　　要：为了有效地对汽车自身可能的运动状态进行预报,并对潜在的行车危险进行预警,开展了汽车运动状态在线测量及预报技术研究。设计了微惯性测量单元,实现汽车运动状态参数在线测量,介绍了汽车姿态解算及其速度积分算法;设计了Kalman滤波器,通过信号融合处理获取汽车运动状态参数的最优估计值;阐述了自回归建模预报方法,并开发了汽车运动状态在线测量及预报软件;最后搭建了车载试验平台并进行了实车道路试验。结果表明:汽车运动状态在线测量及预报技术具有很好的预报效果,为未来开发性能更可靠、效果更佳的汽车主动安全预警系统提供了一定的理论依据和技术途径。In order to predict vehicle motion state and potential danger effectively,on-line measurement and prediction technology for vehicle motion state was developed.Micro inertial measurement unit（MIMU） was designed independently in order to realize on-line measurement of vehicle motion state parameters.Vehicle attitude solution and its velocity integration algorithm were presented and Kalman filter was designed.Through fusion of sensor signals,optimal estimation values of motion state parameters were achieved.Auto-regressive modeling method was built.On-line measurement and prediction software of vehicle motion state was developed.The road test was carried out based on vehicle loading test platform.Results show that on-line measurement and prediction technology for vehicle motion state which can provide an theoretical reference and technical way for future development of active safety warning systems of vehicle has good predicted effect.

关 键 词：汽车工程 汽车运动状态参数 道路试验 在线测量及预报 微惯性测量单元 自回归模型 

分 类 号：U461.91[机械工程—车辆工程]