Research On Electric Vehicle Charging Parking Lot Planning And Management Based On User Behavior

The problem of environmental pollution caused by internal combustion engine vehicle is becoming increasingly prominent.The promotion of electric vehicles will become the general trend.However,confronting the parking and charging demand of electric vehicles,there are many problems in the supporting facilities,such as the lack of quantity,the inefficient utilization,and the mismatch of supply and demand,which result in difficulties of parking and charging.Therefore,it is necessary to combine parking and charging facilities for investigating the planning and management methods of electric vehicle charging parking lot.Based on the actual operation data of electric vehicles,taking the users’ travel and charging behavior as the research object,statistical analysis,mathematical modeling and optimization methods are applied to establish the locating and sizing,and parking space optimal matching method of electric vehicle charging parking lot based on the charging demand prediction.The specific research contents are as follows:Firstly,the charging demand of electric vehicles is predicted based on user behavior.According to the vehicle trajectory and battery state of charge,the feature of users’ travel and charging behavior is studied.The Markov Chain Monte Carlo simulation method is used to predict the spatial-temporal distribution of charging demand and its influencing factors are analyzed.The results show that the peak charging demand of commuter is mainly concentrated in the residential area at night,followed by the working area at noon,and the commercial area has the least charging demand;Factors such as user scale and user travel behavior characteristics have a significant impact on the distribution of charging demand.Secondly,by combining the charging and parking facilities,the locating and sizing method of charging parking lot is studied.Aiming at minimizing the driving and waiting time of users and maximizing the profit of charging parking lot,a double-objective optimization model for locating and sizing of charging facilities is constructed,the solution algorithm of this problem is designed based on genetic algorithm and fuzzy theory.The results show that the model can effectively express and balance the interests of both parties,and the algorithm is effective and feasible,which can provide scientific guidance for the planning of charging facilities.Finally,by considering the sharing of charging parking spaces with the parking demand of the internal combustion engine vehicle,the optimal matching method between user reservation and parking spaces is established.Aiming at minimizing the total cost of users,the collaborative management and optimal scheduling of users’ parking and charging demands are realized by Kuhn-Munkres algorithm.The results show that the optimized matching method can reduce the users’ driving distance and waiting time in peak hours,can improve the success rate of user demand matching,and can improve the total revenue and utilization efficiency of parking lot as well;Sharing of charging parking spaces can provide users with more service hours and reduce the waste of parking resources.In summary,the electric vehicle charging demand prediction,facility locating and sizing,and supply and demand matching methods proposed in this paper have theoretical and practical added values for the planning and management of parking and charging facilities in the era of electric vehicle.