Research On The Method Of Bus Motion State Estimation Based On INS/GPS Data Fusion

With the people's continuous improvement of the safety performance requirements of the automobile,the initiative safety control system has become the focus of research.The vehicle active safety control system controls the stability of the vehicle by obtaining the state parameters in the process of vehicle driving.Due to the limitation of the measurement accuracy and the production cost of the vehicle sensor,some vehicle motion state parameters can not be accurately measured by the vehicle sensors.Therefore,it is an effective method to obtain the state parameters of the vehicle by state estimation.Based on the summary of domestic and foreign scholars on the research of the vehicle motion state estimation and combined with the National Natural Science Foundation of China project,this paper is to use the estimation algorithm to estimate the vehicle motion state information.As the current research on the vehicle motion state estimation is mainly aimed at the passenger car,which is rarely aimed at the bus.Therefore,this paper takes the bus as the research object,carries on the simulation experiment first,and then uses the INS/GPS system to carry out the actual vehicle test,the state estimation algorithm is used to estimate some important state information during the process of bus driving.Firstly,the basic composition and working principle of INS inertial navigation system and GPS system are studied.Secondly,the vehicle two degrees of freedom model is established,and use the classical Kalman filter estimation algorithm to estimate the yaw rate and sideslip angle of the bus.The estimated value is compared with the simulation results obtained by the vehicle dynamics simulation software TruckSim in the same conditions and analyze to verify the effectiveness of the estimation algorithm under linear conditions.Due to the two degrees of freedom vehicle model can not fully describe the dynamic characteristics of the vehicle and the classical Kalman filter can only be applied to the linear system,the seven degrees of freedom vehicle dynamics model and the Dugoff tire model are established.Based on the extended Kalman filter(EKF)estimation algorithm and the unscented Kalman filter(UKF)estimation algorithm,the longitudinal velocity,lateral velocity,yaw rate,sideslip angle and the wheel vertical load of the bus are estimated,and take the estimated values of the EKF algorithm and UKF algorithm to compare with the simulated values obtained by TruckSim in the same conditions to verify the effectiveness and accuracy of the EKF algorithm and the UKF algorithm,and compare the estimation accuracy of the two algorithms.Finally,the actual vehicle experiment is carried out with the INS/GPS system,according to the measured value,using the UKF estimation algorithm to estimate the longitudinal velocity,lateral acceleration and yaw rate of the bus and compare with the measured values to verify the effectiveness of the UKF algorithm in vehicle test conditions.