Research On Control Strategy Of ACC System Of Pure Electric Vehicle

In response to the global energy crisis and traffic safety issues,countries and major auto companies around the world are actively following the trend of intelligent and electrified vehicles,and new energy vehicles are equipped with adaptive cruise control(ACC),which is an intelligent environment-friendly vehicle.ACC is an important part of the advanced driver assistance(ADAS)function.It can recognize the target of effective follow-up in front based on ealizing the constant speed cruise(CC),maintain stable follow-up within a safe distance,and effectively reduce driver fatigue.At the same time,it can also reduce the rate of rear-end collisions,improve driving comfort,and relieve traffic pressure.The main research content of this article:(1)Firstly,the ACC system architecture is analyzed and determined as a hierarchical architecture,which is specifically composed of the upper control and decision-making layer and the lower control layer.The safe distance strategy is analyzed and designed.Based on the existing variable time distance strategy(VTH),an improved VTH strategy is designed considering the driver's dynamic following characteristics,and the simulation experiment of compound working conditions is carried out.Besides,the ACC system working mode is divided into ACC mode and CC mode,namely distance control mode and speed control mode,and the switching strategy between ACC and CC mode is designed,and its feasibility and switching timing are simulated and verified.(2)Secondly,in order to simulate the working platform of a pure electric vehicle equipped with the ACC system,the inverse longitudinal dynamics model of the pure electric vehicle was established based on Carsim,and the vehicle's inverse drive/brake control dynamics model was established in Simulink,and the relationship between the expected acceleration and the brake cylinder pressure and the expected torque is obtained.Also,to prevent frequent switching of the drive and brake actuators at the critical value and extend the service life and driving experience of the actuators,the switching strategy of the drive/brake system was analyzed and designed.(3)Then,based on the algorithm framework of model prediction(MPC),the state space equation of longitudinal kinematics of front and rear vehicles is established as the prediction model,and then linearizes it and discretizes it on this basis.The distance error,relative distance,acceleration of the vehicle,and vehicle acceleration change rate is used as an optimization objective to compose a cost function,and a multi-objective optimization MPC control algorithm that meets the vehicle following safety,ride comfort is established.And use the hard constraint softening method to avoid online solving the problem of no solution to the quadratic programming.(4)Finally,S function in Simulink is used to program the MPC-based multi-objective optimization upper-level control algorithm of the fourth chapter design,and build the Matlab/Simulink and Carsim co-simulation platform.Five different typical traffic scenes were set,and the accuracy and effectiveness of ACC control system for pure electric vehicles developed in this paper were verified through joint comparison simulation with traditional PID control algorithm.