Hybrid Models-Based Cooperative Adaptive Cruise Predictive Control Of Connected Vehicles

With the increase in car ownership,it has caused increasingly serious traffic congestion and threatened traffic safety.At the same time,a large amount of fuel consumption and exhaust emissions have caused serious pollution to the environment;one-third of the cost of a heavy truck in its service life consumed on fuel.If the vehicle can plan a more reasonable gear and speed trend,it can reduce the fuel consumption of the vehicle and improve economic performance.Therefore,it is of great significance to carry out research on collaborative vehicle-based adaptive cruise prediction control based on hybrid model.Since the vehicle models containing gears tend to exhibit typical hybrid characteristics,existing methods based on continuous system modeling or discrete system modeling are difficult to meet the requirements of hybrid control,so innovations from hybrid control modeling and control methods research needs to be further.Therefore,based on MLD(Mixed Logic Dynamic)modeling method,this paper uses the model predictive control method to conduct in-depth research on the cooperative and efficient adaptive cruise control of connected vehicles.The main research contents are as follows:(1)The mixed logic dynamic modeling of connected vehicles based on hybrid system is studied.The definition and principle of mixed logic dynamic system are analyzed,and further explained by two typical hybrid system modeling cases.Finally,the specific process and precautions for establishing mixed logic dynamic model are summarized.(2)Using the HYSDEL(Hybrid System Description Language)language to edit and analyze the mixed logic dynamic model of the connected vehicle,and obtain the HYSDEL program of the model.In MATLAB,the model program is compiled into a hybrid computing model by the HYSDEL editor,and the model feasibility is verified.(3)The predictive control of hybrid systems based on MLD is studied.The predictive control is extended to the mixed logic dynamic system control,and the control effects of the connected vehicle under the PID(P is proportional,I is integral,D is differential)algorithm,the traditional MPC algorithm and the optimized MPC algorithm using the stepped strategy are studied respectively.The research results show that the mixed logic dynamic modeling method can effectively establish a connected vehicle model containing gear information,and the model predictive control method can track the control target well and has a good control effect.The research results of this paper have important theoretical and engineering significance for improving the control effect of cooperative navigation of cooperative vehicles,improving traffic capacity and exploring new methods of vehicle control.