| Title |
A Study on the Charging Demand Forecasting Model for Electric Vehicle Charging Station based on Road Traffic Data |
| Authors |
Hwang Kyu Choi ; Kwang Ho Kim |
| DOI |
http://doi.org/10.5207/JIEIE.2022.36.1.045 |
| Keywords |
Demand forecasting; Electric vehicle(EV); EV charging demand; EV charging station |
| Abstract |
In order to efficiently build and operate an electric vehicle charging infrastructure in response to the rapidly increasing electric vehicles, it is necessary to accurately predict the electric vehicle charging demand. In this study, we set the road traffic as a major factor in determining electric vehicle charging demand and propose the electric vehicle charging demand forecasting model based on the road traffic.
The proposed model suggested in this research primarily predicts the traffic volume of the neighboring area, especially adjacent roads where the charging station is located, and estimates the number of electric vehicles and their charging demand by using the relevant electric vehicle statistics and the historical charging data. As a result of simulated verification of the proposed model for the expressway rest area (Jukam rest area, Seoul direction), it shows an accuracy of 2-3% and is expected to be used as one of the traffic-based models in predicting electric vehicle charging demand. |