Research On Planning Control And Lateral Stability Control Of Distributed Drive Vehicles

With regard to the frequent occurrence of road traffic accidents caused by drivers’ inattention and inability to make timely and accurate judgments under hazardous conditions,in the context of the electrification and intelligence of the automotive industry,this thesis has taken distributed drive electric vehicles as the research platform to study local trajectory planning and trajectory tracking control in the intelligent driving systems under the extreme working conditions of emergency obstacle avoidance.To realize the automatic tracking of the optimal obstacle avoidance trajectory by automatically controlling the front wheel angle of the vehicle,And to prevent vehicle instability,further research has been conducted on its lateral stability control integration.Aiming at the problems of power loss caused by single-side wheel braking in traditional stability control,and poor driving experience caused by frequent correction of front wheel angle due to steering control,the rear wheel torque vector distribution has been used to generate additional yaw torque for vehicle deviation correction and trajectory tracking optimization.The main research contents of this paper are as follows:Firstly,Research on the three main contents of local trajectory planning,trajectory tracking control,and lateral stability control to be studied,as well as the current status of active emergency obstacle avoidance technology in the industry at home and abroad has been conducted.This paper through the research to understand the current mainstream control strategies and methods used,and establish the technical route.Secondly,for the design of subsequent planners,controllers,and state observers,a linear two degree of freedom vehicle dynamics model,a nonlinear seven degree of freedom vehicle dynamics model,and a "magic formula" tire model have been established.This paper have conducted comparative verification of vehicle parametric dynamics simulation.It has meet the accuracy requirements to provide a model basis for subsequent research.Thirdly,considering the requirements of computational complexity,real-time performance,and accuracy,a local trajectory planner and a trajectory tracking controller have been designed based on model predictive control.The planner finally outputs the discrete points of the obstacle avoidance trajectory in the quintic polynomial fitting manner.The trajectory tracking controller controls the front wheel angle for tracking.And a two-level PID controller has been designed for longitudinal control to achieve vehicle speed retention.A parameter adaptive controller based on fuzzy control has been designed to output the optimal predictive time domain and lateral position deviation weight coefficients for model predictive control according to the vehicle speed and lateral position deviation.The final simulation verifies the effectiveness of fuzzy adaptive parameter adjustment for trajectory tracking improvement and the feasibility of the planning and control strategy based on improved model predictive control.Fourthly,to address the problem of trajectory tracking failure caused by vehicle lateral instability under extreme operating conditions,a lateral stability controller based on layered control has been designed: the upper layer yaw moment controller is based on boundary layer sliding mode variable structure control,with the center of mass sideslip angle and yaw rate as the control objectives.The boundary layer method is used to deal with the chattering problem of sliding mode control,and the additional yaw moment is ultimately output.The lower layer torque vector distribution controller is based on multi-objective optimization,with the average and variance of the tire load rate as the control objectives.Torque vector distribution acts on the rear wheels and optimal driving and braking torque of four wheels is solved.Finally,the integrated simulation verification of limit simulation conditions and trajectory tracking control has been established,and it has been concluded that integrated control can prevent vehicle instability and optimize trajectory tracking effects.Fifthly,based on vehicle dynamics modeling,the simulation platform has been established,and the joint comparative simulation verification of the involved obstacle avoidance local trajectory planner,trajectory tracking controller and integrated lateral stability controller was carried out.Finally,it has been concluded that the planner can timely plan the optimal trajectory for obstacle avoidance,and the vehicle can track the obstacle avoidance trajectory by controlling the front wheel angle.Torque vector distribution can prevent instability while optimizing trajectory tracking control effects.Finally,the full text has been summarized and prospected.In this paper,for the extreme conditions of emergency obstacle avoidance,model predictive control has been used for planning and control,and fuzzy control has been used to adaptively improve model predictive control parameters.Layered control integration has been used to control vehicle lateral stability.The simulation verifies that the trajectory tracking effect can be optimized through the improvement of fuzzy tuning parameters,and the trajectory tracking failure caused by vehicle instability can be prevented after the integration of lateral stability control.It has theoretical and engineering significance in the field of intelligent driving planning and control and dynamic integrated control technology.