Research on On-line Measurement and Prediction for Vehicle Motion State

摘要：

The research on on-line measurement and prediction technology for vehicle motion state is developed in view of shortage that the existing active safety warning systems, which focus on monitoring and warning, lack prediction process for vehicle motion state. MIMU (Micro Inertial Measurement Unit) is designed independently in order to measure vehicle motion state parameters. Then vehicle attitude and velocity integration algorithms are presented and Kalman filter is designed to accomplish sensor signals fusion in order to achieve optimal estimation of vehicle motion state parameters in consideration of low precision of MEMS (Micro-Electro-Mechanical Systems) sensors. Auto-Regressive modeling method is discussed in detail. On-line measurement and prediction software for vehicle motion state is developed based on VB2005 and NI Measurement Studio as well as Matlab, NET Builder. The road test for online measurement and prediction of vehicle motion state is carried out based on vehicle on-board test platform. The test result receives good effect, which testifies the validity and feasibility of on-line measurement and prediction research for vehicle motion state.

关键词： vehicle motion state parameters on-line measurement and prediction Micro Inertial Measurement Unit Auto-Regressive Model Road test

作者: Liu Jun Wang Sumei Pan Ke Xie Jun Wang Yun Zhang Tao

作者单位: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013,China

会议类型: 国际会议

会议名称: 2010 International Conference on Digital Manufacturing and Automation(2010 数字制造与自动化国际会议 ICDMA 2010)

会议地点: 长沙

会议语种:英文

页码: 247-250

在线出版日期: 2010-12-18（万方平台首次上网日期，不代表论文的发表时间）