Research And Design Of Charging Guidance Strategy For Electric Vehicles

The current impediment to the advancement of electric vehicles is a combination of unfavorable elements,such as an inadequate amount of charging infrastructure,a lack of battery life,and the incapability of the charging service platform to furnish efficient charging station data.At this stage,the most feasible way to solve the charging problem of electric vehicle users is to design an effective and feasible electric vehicle charging guidance model,algorithm and strategy,and plan a reasonable and feasible driving path for users as well as a charging station that matches users’ needs.In this paper,we analyze the traffic data,the charging requirements of users,and the distribution of charging stations to create suitable guidance plans for electric cars.The primary research topics are as follows:(1)A proposal for an advanced grey wolf algorithm(PSO-GWO)based on a top-notch reverse learning process is put forward.This paper designs an improved Grey Wolf algorithm(PSO-GWO)to enhance the convergence performance of the traditional one in addressing the charging guidance issue of electric vehicles.Nonlinear parameters are incorporated and the position equation is modified with the elite reverse learning mechanism to initiate the population.The PSO-GWO algorithm outperforms the traditional Grey Wolf algorithm and other algorithms in the benchmark function.It can rapidly reach the optimal solution,surpassing the local optimum by a considerable margin,and its convergence speed is also quicker.(2)To begin,a quantitative assessment of electric vehicle users;charging times is conducted,leading to the formation of a charging time minimization model.Subsequently,the time-of-use electricity price incentive mechanism and the optimal charging time recommendation strategy are employed to create a charging guidance model with the aim of achieving the lowest unit electricity cost.Finally,the model is used in the road network of Ganzhou City for an example study.This paper’s charging guidance strategy has been demonstrated to be capable of recommending the charging station with the least amount of time and cost,and plotting the charging route.(3)A fast charging guidance strategy for electric vehicles is designed considering the driving direction characteristics of the user’s travel destination.Considering the user’s travel demand for the destination,a geometric function-based algorithm(AGF)is proposed.And this algorithm adds the user’s travel direction feature in the process of charging station selection,and expresses the consistency of the travel direction trend between the charging path and the destination by designing a geometric quantitative expression.The simulation results show that the AGF algorithm is significantly more efficient than the traditional shortest distance algorithm,and can locate the charging station closest to the destination.Moreover,it is significantly faster than the shortest distance algorithm and its upgraded version in terms of running time.(4)Design electric vehicle charging recommendation interface.In view of the shortcomings of the traditional charging station recommendation APP that can not effectively reflect the specific information required for charging,this paper designs a charging graphical interface composed of power warning,charging information and path planning based on the user’s time,cost and target requirements for charging station.First of all,the electric vehicle electric quantity warning board is designed,and the function relationship between SOE and SOC is fitted,and the remaining electric quantity is estimated by the battery SOE;Finally,the charging recommendation interface is designed by using Matlab App Designer to effectively relieve users’ charging anxiety.