Abstract

The location of electric vehicle charging facilities is of great significance in promoting the use of electric vehicles. Most existing electric vehicle location models, including the flow refueling location model (FRLM) and its flexible reformulation (FRFRLM), are based on flow demand. At present, these models cannot effectively deal with large-scale traffic networks within a limited time, and there has been little comparison of their relative benefits and limitations. Additionally, there have been few evaluations of the actual construction and location of charging facilities in cities. This paper describes an algorithm that can solve the large-scale transportation network problem within a reasonable time. Using this algorithm, the FRLM and FRFRLM models are compared in a case study focused on Jiading District, Shanghai, China, which provides some direction for the future development of flow demand models. Finally, to evaluate the actual construction of urban charging facilities, this paper presents an algorithm that can map the actual charging facilities to the transportation network, and compares the actual construction situation with the model output. This enables a comprehensive evaluation of the actual construction of charging facilities and provides guidance for future construction.

Highlights

  • Published: 28 April 2021With continued economic development, increasing attention is turning to the problem of environmental pollution

  • The reason is that when the total number of site selection points is large, flow refueling location model (FRLM) takes a long time to filter out the combinations that allow vehicles to travel between OD pairs

  • When solving large‐scale problems, FRFRLM is more e cient than FRLM

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Summary

Introduction

With continued economic development, increasing attention is turning to the problem of environmental pollution. In terms of research on electric vehicle charging facility planning based on flow demand, the flow refueling location model (FRLM) and its variants cannot effectively deal with large-scale traffic networks within a short period of time [14]. We used the latitude and longitude data associated with the parking and charging of electric vehicles to develop an algorithm that maps real charging facilities to the transportation network, and compared the results with the output of FRLM and FRFRLM to evaluate the current construction of electric vehicle charging facilities. The. Section 6 evaluates the current status of charging facilities in Jiading District, Shanghai, based on the results of the model output and the result of mapping real charging facilities to the transportation network. Section seven analyzes and summarizes this paper and looks forward to future research

Literature Review
Flow Refueling Location Model
Flexible Reformulation of the Flow Refueling Location Model
Algorithm for Solving Large-Scale Transportation Network Problems
Algorithm for Mapping
Case Study
Using FRLM and the Proposed Algorithm to Solve the Problem
FRLM: FRLM
Comparative
Comparative Analysis of Coincidence Rate of Model Site Selection
Comparative Analysis of Models
Coincidence ofand andlocation location points firstnumbers stage for various
Summary the Model
Evaluation
Summary of the Model Comparison
13. Charging
Conclusions and Future charging facilities in Jiading
Conclusions and Future
Full Text
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