Research On Longitudinal And Lateral Control Of Intelligent Vehicle With The Motion Stability

In recent years,the research of intelligent vehicles has attracted more and more attention as a new research hotspot after the new energy vehicles.And,vehicle motion control is the basic problem to be considered in the research of intelligent vehicle.First,we design model predictive control algorithm based on dynamics model of vehicle and linear quadratic regulator to realize the lateral control of intelligent vehicles.In this paper,three degrees of freedom vehicle model is used as the basic dynamic model,and it is linearized as predictive model.The control target is the deviation of the path and the lateral velocity of the vehicle,also the output is front and rear wheel angle.In order to enhance the yaw stability of vehicle,a linear quadratic regulator is used to calculate the additional yaw moment to control yaw rate.Simulation results show that the proposed model predictive control algorithm performs effectively.Then in order to reflect the driving conditions of intelligent vehicles more completely,we design longitudinal control of vehicles.The sliding mode control is used to calculate the total longitudinal force,then the additional yaw moment and the total longitudinal force is distributed to each wheel through the longitudinal force distribution strategy,and the wheel torque is obtained by Dugoff tire model and wheel rolling model.The longitudinal and lateral control block diagram is designed,and simulation results show that the proposed strategy performs effectively.Finally,in reality the sideslip angle of vehicle is difficult to be measured directly,so we use the Kalman Filter to estimate the sideslip angle,and as the input is sent to the vehicle's controller.Simulation results show that the proposed Kalman Filter performs effectively.