Research On Electric Vehicle Charging Route Planning Method In Multi-information Interconnected Environment

With the rapid increase in the number of electric vehicles and charging stations / piles,due to the dual characteristics of vehicles and moving loads,the driving characteristics and charging behavior of electric vehicles will have an interactive effect on the transportation network and the power grid.Based on the convenience of user travel,comprehensively considering traffic conditions,charging station operation status,and power grid operation quality,a route planning and charging navigation strategy for electric vehicles in a multi-information interconnected environment is proposed.Mainly include the following:For electric vehicles,transportation networks,power grids and charging stations,the attribute characteristics of each part and the coupling relationship between the four are analyzed,and models including electric vehicle models,road transportation network models,power grid models and charging station models are established and are based on multiple layers Network theory has established a "vehicle-road-network-station" coupling model.Established a network operation data prediction model for charging stations,and provided reference information for where electric vehicles are charged when there is a demand for charging.First of all,we use the obtained open source information of electric vehicle charging stations in the planning area to analyze the correlation between the number of free and busy charging stations and meteorological factors,day types,surrounding road conditions and other factors based on the real data of the charging station network.Then,the deep learning method is used to predict the number of charging piles in use in the charging station in real time,and provide users with suggestions on the effective charging period of each charging station.This paper established the user's preference model for charging stations.Using the charging data of charging stations of electric vehicle users and the data of gas stations of potential users,mining the user's historical selection behavior,analyzing the user's preference for different charging stations,a user charging station selection preference model based on collaborative filtering is proposed.A multi-information coupled charging route planning method is proposed.First,comprehensively consider the road network congestion,power grid operation,charging station operation,user interests and preferences,and establish the overall structure of the electric vehicle charging path planning system.Then,based on the fuzzy membership function method,the weights of each objective function are determined,and the weights of the objective function are dynamically adjusted according to the current state of the transportation network and the power grid.Finally,the effectiveness of the proposed charging navigation strategy is verified by simulation in the planning area.