Research On Estimation Algorithm Of Vehicle Dynamics State Parameters

With the continuous development of automotive technology,the stability of vehicles has attracted more and more attention from engineers.For the research of vehicle stability,it is necessary to use sensors to obtain real-time state information of the vehicle,such as the side slip angle of the center of mass.However,due to the limitation of the cost of automobile development,the current measures are to use estimation methods to estimate the information that is not easy to measure based on the available vehicle status information.Common vehicle state estimations include Sliding Mode Observer,Luenberger Observer,Nonlinear Observer,Kalman Filter,etc.Among them,Kalman filter and its improved algorithm have become the research focus of scientific researchers because of the high accuracy of estimation stability.Aiming at the problem of vehicle dynamics state parameter estimation,this paper conducts research on estimation algorithms.First,the 7-degree of freedom vehicle model and the 3-degree of freedom vehicle model are built,which are the basis of the vehicle dynamics model.On the basis of the vehicle model,Magic tire and Dugoff tire models are built respectively.In order to verify the accuracy of the built model,this article uses the vehicle dynamics simulation software Car Sim for simulation.The results show that the model used in this article can effectively estimate the tire force.Secondly,aiming at the problem of estimating the body sideslip angle,the estimation models based on the state observer,SMO and EKF are established respectively,and the simulation results verified the superiority of EKF.Aiming at the longitudinal vehicle speed problem,an estimation model based on the recursive least square method(RLS)is established.The simulation shows that the RLS method performs better than the maximum wheel speed method.Aiming at the problem of road adhesion coefficient estimation,the estimation models based on adhesion margin method and EKF are established respectively.The simulation results show that the EKF method has small fluctuations and is more stable.Next,considering the large error of EKF when calculating nonlinear system problems,this paper uses the square root cubature Kalman filter(SRCKF)method to estimate the body sideslip angle.Aiming at the problem that the error covariance matrix of CKF may be non-positive definite and leading to the interruption of filtering,QR decomposition is used to calculate the error covariance matrix to solve the problem of non-positive definite matrix.Then this article established the estimation model of side slip angle based on SRCKF centroid.Finally,this article uses the vehicle to carry out the actual road test,collects the test data of the shifting working condition,the circle working condition and the serpentine working condition,and simulates the EKF,CKF and SRCKF offline.Test and simulation results verify the validity,feasibility and accuracy of the SRCKF.