Design And Study Of Estimation Algorithm For Vehicle Velocity Based On AMESim

At present, the car’s active safety and handling stability has been paid widespreadattention to. Vehicle active safety control systems, such as Antilock Braking System(ABS), Traction Control System (TCS) and Electronic Stability Program (ESP), caneffectively improve the security and stability of the car in motion. The effectiveimplementation of these vehicle active safety control systems depends on the precisevehicle status information. The vehicle longitudinal velocity and lateral velocity playthe vital role in active safety control system. Due to technical limitations and othereconomic reasons, the vehicle longitudinal velocity and lateral velocity can not bedirectly obtained from the vehicle-mounted sensors. Therefore, in this paper theestimation algorithm of longitudinal vehicle velocity and lateral vehicle velocity isdesigned based on estimation theory.In the design of the speed estimation algorithm, a lot of real vehicle test data andto test the estimation algorithm are needed. So it is important to chose a suitablesimulation software to establish an accurate vehicle model for obtaining test datainstead of the real vehicle.AMESim software is advanced engineering systemmodeling and simulation software which can provide users with a complete systemsengineering design platform. At the same time, the graphical modeling method is usedin this software. There is abundant element database in AMESim, and it containsevery subject. With these advantages, the user can build a more complicated subjectareas system model and come out from the multifarious mathematical models. It isfast and convenient.Therefore, firstly in this paper the15degrees of freedom vehicle model isestablished in AMESim, and research and analysis on the dynamic performance of thevehicle model are done in several simulation conditions. This model can provide agood source of test data for the design of the speed estimation algorithm and providesan effective base model for the speed estimation algorithm validation.Secondly, a precise eight degrees of freedom vehicle dynamics model isanalyzed and established based on the algorithm needs. The model using the magicformula (MF) tire model is used in the model, which can improve the accuracy of thevehicle dynamics model in the limit working conditions. And then the estimationalgorithm is designed based on the dynamic model. In the test, the rode is assumed tobe a level road, thus the eight degrees of freedom model can be simplified for the seven degrees of freedom vehicle dynamics model, and the vehicle speed UKF filterestimation algorithm is done.Finally, combined with the15degrees of freedom vehicle model established inthe AMESim and using the good co-simulation platform provided by AMESim, thesimulations to the estimation algorithm are done under various conditions. The resultsshow that the UKF vehicle velocity estimation algorithm is simple and the simulationresults are good. AMESim can provide a good simulation platform for the design andverification of the speed estimation algorithm,and the co-simulation results is good.