| According to statistics from the Ministry of Public Security,by the end of 2022,the number of new energy vehicles in the country reached 13.1 million,a year-on-year growth rate of 67.13% in 2021.The government has introduced a large number of policies to promote the development of charging and replacing facilities,and the current comprehensive vehicle pile ratio in China is 3:1,far lower than the planned 1:1 target,and the coverage of China’s highway charging facilities is lower.Therefore,how to determine the charging demand of electric vehicles in the expressway and give the site selection planning method of charging and swapping power station needs to be solved urgently.In view of the above problems,this paper studies the charging needs of highway electric vehicle users,provides a site selection planning method for highway charging and swapping stations,and provides a charging path planning scheme for highway electric vehicles,as follows:(1)Firstly,the relevant theories of site selection of electric vehicle charging and swapping stations are introduced;Then,a single model of highway electric vehicle was established to lay a foundation for the site selection and planning research of charging and swapping power stations.Finally,the gray prediction model is used to predict the ownership of electric vehicles.(2)Aiming at the charging demand problem of highway electric vehicle users,a highway electric vehicle charging demand model based on vehicle flow and fuzzy reasoning method is established.Firstly,the influencing factors of highway electric vehicle charging are analyzed from the aspects of users’ travel characteristics and road network.Secondly,according to the characteristics of the road network,a traffic flow calculation method based on the Link Transmission Model(LTM)is proposed.Then,a user charging probability and power consumption model based on adaptive fuzzy neural network algorithm is established to analyze the influencing factors of user charging.Finally,the charging load demand of electric vehicles is obtained through the Monte Carlo method.The simulation results verify the effectiveness of the proposed prediction method and provide theoretical support for the site selection planning of charging and swapping stations.(3)Aiming at the site selection of highway electric vehicle charging and swapping power stations,a site selection model based on the expansion network of charging and swapping stations is established.Firstly,considering the randomness of the road network,the extended network road model of single-path driving is established,and the fixed capacity model is established.Then establish the lowest cost target planning model;Finally,the proposed method uses the improved genetic algorithm to solve the objective function to obtain the site selection point.The results show that the model and algorithm are feasible.(4)The charging path optimization method for highway electric vehicle users is proposed,and firstly,the energy consumption model of the user’s driving state is established by analyzing the influence of driving speed and vehicle accessories on energy consumption.Then,taking the shortest travel time and minimum cost of users as the objective function,the multi-objective function is transformed into a single objective function by using fuzzy mathematics.Finally,the gray wolf optimization algorithm is used to obtain the optimal charging path. |
