Co-Simulation Research Of Adaptive Cruise System Control Strategy Base On Model Predictive Control

Due to the continuous growth of car ownership in recent years,the road congestion,frequent traffic accidents and environmental pollution caused by it are always bothering people.In this context,the automotive industry began to gradually transform to the new "four modernizations" mode,and the research on intelligent auxiliary technology related to electric vehicles is also in full swing.With the increasing demand for driving experience,the development and research of adaptive cruise system,as an intelligent automatic driving control technology,has attracted much attention.But at present,the research on the application of this system in pure electric vehicles is relatively less in China,and due to the change of power transmission route,the control strategy of traditional fuel vehicles is difficult to be directly grafted onto pure electric vehicles.Therefore,it is of great significance to study the application of adaptive cruise system in pure electric vehicles from three aspects of people,vehicles and roads.In this thesis,a hierarchical adaptive cruise control strategy based on model predictive control(MPC)is proposed.The simulation results show that the strategy has good control effect.The main research contents are as follows:(1)Based on the hierarchical theory,the overall structure of the control strategy of adaptive cruise system is established and the main functions of each layer are determined.According to the working mode of the system,it is divided into two modes: constant speed cruise and car following cruise,and the corresponding mode switching control strategy is formulated;the driver intervention priority mechanism is designed to ensure the priority of the driver under special circumstances.(2)The model of safe vehicle spacing based on fixed headway algorithm is established,and the upper control model is established to describe the mutual longitudinal kinematic characteristics of workshops.On this basis,a prediction model based on MPC control strategy is established to analyze the control requirements,and the objective function and constraint conditions are established to solve the expected acceleration.(3)Based on the vehicle running equation,the vehicle reverse longitudinal dynamic model is established,including braking mode and driving mode.Aiming at the drawback of frequent switching back and forth between braking mode and driving mode in the control process,the switching strategy between the two modes is improved.According to the characteristics of pure electric vehicle,the motor type is selected,the simulation model is established and the corresponding control method is formulated(4)According to the different working conditions in the process of car following,a joint simulation platform is established by Carsim and MATLAB/Simulink to build a pure electric vehicle model,and four common road conditions are designed for simulation to verify the effectiveness of the proposed control strategy.The simulation results show that the proposed control strategy can effectively control the driving process of the vehicle,and at the same time,it can take into account the safety of vehicle following and ride comfort.