Research On Path Tracking And Stability Control Of Distributed Drive Autonomous Vehicles

The rapid development of automobile industry has brought great convenience to people’s life,but traffic congestion and environmental pollution caused by the popularity of automobiles are increasingly serious,so intelligent,networked,electric is considered to be the development direction of the automobile industry in the future.As one of the key technologies in the development of intelligent vehicle,the path tracking control technology of unmanned vehicle is the technical premise of realizing unmanned driving.And the distributed drive electric vehicle has become one of the mainstream drive forms of electric vehicles because of its excellent performance and has a good application prospect.So based on the distributed drive electric vehicle as the research object,in view of the automatic driving path tracking control of the vehicle and the vehicle driving stability problems in the process of tracking,using a distributed drive electric motor torque independently controllable advantage,distributed drive path tracking and stability of the automatic vehicle control strategy research,In order to improve the tracking accuracy of the path tracking control of autonomous vehicles,and improve the driving stability of the vehicle in the tracking process.Firstly,the dynamics modeling of distributed drive autonomous vehicle was analyzed.In order to reduce the calculation difficulty,a vehicle dynamics model with seven degrees of freedom including lateral,longitudinal,yaw and four wheels rotation was established based on reasonable simplification assumption.The nonlinear tire model based on magic formula was established,and the characteristics of the tire model were analyzed,and the linear working area of the tire was determined.According to the research needs,the hub motor model is established,and the parameters of the established hub motor model are matched.Secondly,on the basis of the established vehicle dynamics model,the path tracking controller of autonomous vehicle based on model predictive control are established,and the designed path tracking control strategy is simulated and verified by building Carsim and MATLAB/Simulink co-simulation platform.In this paper,the influence of model predictive controller’s preview step size on tracking control effect is discussed,and the conclusion is drawn that the controller with fixed preview step size is difficult to give consideration to the control precision and driving stability of vehicle path tracking,and the research on adaptive control of preview step size is carried out to solve this problem.Considering the yaw speed and tracking deviation of the vehicle as the control input and the step size of preview as the output,fuzzy control theory was used to adjust the output value of the step size of preview in real time to realize the adaptive control of the step size of preview.In order to verify the control effect of the designed adaptive controller,different vehicle speeds were selected to simulate the control effect.The results show that the model predictive controller based on the adaptive control strategy of preview time can significantly improve the control accuracy and driving stability of the vehicle under different driving conditions.The influence of stability control parameters such as yaw rate and center of mass slip angle on vehicle stability is analyzed,and the ideal values of the control parameters are analyzed and calculated.Based on the sliding mode variable structure control strategy,a yaw stability controller with joint control of yaw angular velocity and center of mass slip angle is established.For the torque distribution problem of the lower layer,the longitudinal driving force demand and yaw moment demand of the upper layer are combined with the correlation.Constraints establish a four-wheel torque optimal distribution controller to optimally distribute torque.Considering the influence of vehicle speed changes on driving stability,a PI controller is designed to follow the longitudinal vehicle speed.And through the simulation experiments under the closed-loop double line-shift path and the open-loop sinusoidal transfer input,the results show that the designed yaw stability control strategy can significantly improve the driving stability of the vehicle.Finally,in order to verify the effectiveness of the proposed path tracking control and stability control strategy of distributed driven autonomous vehicle,a co-simulation platform based on Carsim and MATLAB/Simulink was built.The control effect of the integrated path tracking and stability control strategy was simulated by selecting three different adhesion conditions of dry asphalt pavement,wet asphalt pavement and ice and snow pavement.The results of co-simulation show that the model predictive path tracking control algorithm,yaw moment control algorithm and four-wheel torque optimal allocation control algorithm have good control effects.Compared with the vehicle without stability control strategy,the vehicle achieved better performance in the aspects of path tracking accuracy and driving stability when carrying out path tracking driving under three road conditions.