Modeling And Simulation Of Large-Scale Electric Vehicle Group Considering The Mode Of Autonomous Driving-Shared Travel

Now in the process of energy transition,travel upgrades such as electric vehicles,shared travel and autonomous driving continue to affect the energy structure of the transportation.As a new type of transportation,electric vehicles can be connected to the power system,and their related applied research have received extensive attention.For these studies,charging data is their important research basis.However,the current permeability of electric vehicles and the popularity rate of charging facilities are still very low,which is far from the traffic scene under the background of future travel upgrades.It is difficult to directly obtain the charging data of large-scale electric vehicle group required for research in the current actual scene.To this end,this thesis comprehensively considers the factors such as the traffic network,charging stations and travel modes that can affect the behavior of electric vehicles,and conducts a quantitative analysis of the driving and charging states of electric vehicles.Furthermore,the multi-agent technology is used to establish an electric vehicle group simulation model that can adapt to the future travel scene,so that the charging data in the future scene of large-scale electric vehicle access can be obtained through simulation methods.The model contains four agents: map agent,time agent,charging agent and vehicle agent,and introduces the algorithm flow of each agent in detail.At last,this thesis uses the established simulation model and takes different travel scenes as examples to analyze the impact of travel upgrades on the charging characteristics of electric vehicle groups.The charging load of the electric vehicle group is found obedient to logarithmic normal distribution,and the increase in the permeability of electric vehicles and the proportion of autonomous driving-shared travel will increase the daily average charging load of the electric vehicle group.However,unlike the relationship between the daily average charging load and the permeability basically maintaining the same proportional increase,as the proportion of autonomous driving-shared travel increases,the increase in the daily average charging load of electric vehicle group will continue to decrease.The work of this thesis is helpful to understand the changes brought about by the travel upgrades from the perspective of electric vehicles.The established multi-agent simulation model of large-scale electric vehicle group can generate the charging data required for related applied research and can provide suggestions and help for the future modeling and simulation work of electric vehicle group.