Charging Path Planning Model For Electric Vehicles In The Environment Of Mutual Assistance Trip

In recent years,the number of electric vehicles has grown rapidly.However,the construction of charging facilities has obviously lagged behind the growth of electric vehicles,which resulting in an imbalance between charging supply and demand.It seriously affects the convenience of electric vehicle users.At the same time,in the context of "dual carbon",electric vehicles will still be strongly supported,whose ownership will continue to maintain a high growth trend.The charging contradiction will become increasingly prominent.It is a feasible solution for electric vehicle users to alleviate this contradiction,using communication technology to plan a reasonable charging path.In this thesis,a mutual assistance trip environment is created by building the framework of the mutual assistance trip system.Combined with road condition information,charging station service information and vehicle mutual assistance information,an electric vehicle charging path planning model considering the mutual assistance information is established.On this basis,a safety evaluation model is established.The model and results are verified and analyzed through numerical simulation experiments and driving simulation experiments.The research results are significance in solving the spatiotemporal imbalance of electric vehicle charging supply.The specific research contents of this thesis are as follows:(1)The concept of mutual assistance for electric vehicle travel is proposed,and a framework of mutual assistance trip system is built,which creates a mutual assistance trip environment for electric vehicle users as the technical background for the full-text research.Then the traffic network model,queuing time model and the energy consumption prediction model are established as the basis for the subsequent establishment of the charging path planning model.(2)In order to guide the charging and provide alternative paths for electric vehicle users,an electric vehicle charging path planning model considering mutual assistance information is established.Electric vehicle users generally have different charging needs.According to whether the mutual assistance center knows the user’s travel destination,two scenarios for users are designed,which are random and planned respectively.Scenario 1 aims to minimize the total time cost of users,and uses information entropy theory to quantify mutual assistance information into mutual assistance information risk factor θ to adjust the cost weights.A genetic algorithm based on priority coding is proposed to solve the model of scenario 1.The numerical simulation results show that after users participate in the mutual assistance,the total time cost is significantly reduced,indicating that the mutual assistance effect is good.Scenario 2 aims to minimize the total travel cost of users,and proposes a mutual assistance selection factorμ to adjust the weights of each cost,and uses the genetic algorithm based on the quadrant division method to solve the problem quickly.The numerical simulation results show that when the value of the mutual assistance selection factor changes,the total cost of the path will change accordingly,indicating that the optimal charging station and path selection corresponding to different user preferences are different.(3)In order to verify the safety of the charging path,an electric vehicle charging path safety evaluation model is established.Firstly,a set of safety evaluation index system is established.A total of 18 indexes is selected from the four dimensions of road traffic,natural conditions,abnormal driving characteristics of mutual assistance vehicles and unique factors of electric vehicles.The first principal component analysis method was used to objectively determine the weights of the two categories of the road traffic and abnormal driving characteristics of mutual assistance vehicles.Then calculate the comprehensive score of safety level together with the other two categories of indicators.Finally,the safety level of the charging path is divided into three levels: low,medium and high.(4)In evaluating the safety of electric vehicle charging,the use of driving simulators for simulation has unique advantages over numerical simulations.In order to explore the different path selection preferences of different driver types.Firstly,based on the driving simulation data,the driving style types of drivers are classified into three categories: aggressive,balanced and conservative.Secondly,each driving style is extracted from the path samples.The mutual assistance selection factor group corresponding to the member type is used as the key parameter of the objective function of the charging path planning model.Finally,a driving simulation test of the electric vehicle charging process is designed to evaluate the safety level of the charging path.It shows that after the path planning and charging guidance of the mutual assistance center,the overall safety level of the paths in the mutual assistance experimental group is significantly higher than that in the non-mutual assistance control group.