Research On Hybrid Charging Scheduling Strategies Of Electric Vehicles

Modern transportation is developing rapidly,but a series of problems such as global warming caused by energy consumption and pollutant emissions.Electric vehicles(EV)have become the main trend of the future development of the automotive industry due to its characteristics of zero emissions,low noise,and high energy efficiency.However,The current user experience of electric vehicle charging is far from being expected.That’s because electric vehicles are often disorderly and randomly connected to the charging interface at the current stage.At the same time,there are hybrid charging modes of reserved charging and queued charging.This charging scheduling issue needs to be addressed immediately.Based on above description and discussion,this paper addresses the hybrid-mode scheduling problem in the transition phase of electric vehicle charging scheduling development under the electric vehicle driving mode,and discusses and studies the management and allocation of charging pile resources in electric vehicle charging stations,switching of charging modes,and considers the personal driving plans and charging satisfaction of charging scheduling issues.In order to solve the issues of charging resource competition and charging scheduling when there are two types of charging modes,namely,reserved charging and on-site queuing charging.This paper proposed a charging pile allocation strategy based on the charging success rate in the charging station.Firstly,this paper determines the overall scheduling time window according to the competition of resources,and based on the historical charging data of charging station users,the proportion of charging piles that different modes of users can access in the scheduling slot is reasonably allocated using reinforcement learning algorithm.Secondly,compares the queuing time of queued charging users and appointment waiting time to intelligently switch the charging mode;through reasonable numerical and system simulation results to verify that the scheduling algorithm in this paper balances and improves the user’s charging experience under different charging modes during the transition phase,and improves the flexibility of the user’s charging mode selection,At the same time,the simulation results also show that the algorithm improves the resource utilization rate of the charging pile.In the driving mode there will be a shortage of charging facilities in the peak period of electric vehicle charging,and the centralized charging scheduling of electric vehicles based on the driving plan needs to resolve the contradiction that takes into account the user’s driving plan and differentiated charging satisfaction.This paper proposes a queuing waiting charging scheduling strategy based on the limited waiting space in the charging station;moreover,Improving and Proposing a charging scheduling strategy combining advance booking and on-site scheduling.Firstly,according to the battery power level of different electric vehicle users and the distance to the destination,the reserved charging set is selected,and a queuing mechanism is introduced.Secondly,dispatching electric vehicles to different charging stations for on-site queuing charging or booking charging,effectively improving users’ overall charging satisfaction and charging service success rate.Finally,The optimization model corresponding to the above scheduling strategy is solved by genetic algorithm,and the simulation results show that the above strategy effectively reduces the average charging waiting time and the average charging detour cost of users.