Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function
As the adoption of electric vehicles (EVs) rapidly increases, the expansion of charging infrastructure has become a critical issue. Unlike internal combustion engine vehicles, EV charging is sensitive to factors such as the time and location for charging, depending on the charging speed and capacity...
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MDPI AG
2025-03-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/4/192 |
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| author | Dayeon Lee Dong Sik Kim Beom Jin Chung Young Mo Chung |
| author_facet | Dayeon Lee Dong Sik Kim Beom Jin Chung Young Mo Chung |
| author_sort | Dayeon Lee |
| collection | DOAJ |
| description | As the adoption of electric vehicles (EVs) rapidly increases, the expansion of charging infrastructure has become a critical issue. Unlike internal combustion engine vehicles, EV charging is sensitive to factors such as the time and location for charging, depending on the charging speed and capacity of the battery. Therefore, recommending an appropriate charging station that comprehensively considers not only the user’s preference but also the charging time, waiting time, charging fee rates, and power supply status is crucial for the user’s convenience. Currently, charging station recommendation services suggest suitable charging stations near a designated location and provide information on charging capacity, fee rates, and availability of chargers. Furthermore, research is being conducted on EV charging station recommendations that take into account various charging environments, such as power grid and renewable energy conditions. To solve these optimization problems, a large amount of information about the user’s history and conditions is required. In this paper, we propose a real-time charging station recommendation method based on minimal and simple current information while driving to the destination. We first propose a preference objective function that considers the factors of distance, time, and fees, and then analyze the recommendation results based on both synthetic and real-world charging environments. We also observe the recommendation results for different combinations of the weights for these factors. If we set all the weights equally, we can obtain appropriate recommendations for charging stations that reflect driving distance, trip time, and charging fees in a balanced way. On the other hand, as the number of charging stations in a given area increases, it has been found that gradually increasing the weighting of charging fees is necessary to alleviate the phenomenon of rising fee rates and provide balanced recommendations. |
| format | Article |
| id | doaj-art-709c6ce3248b484e959bf41b3528318b |
| institution | OA Journals |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-709c6ce3248b484e959bf41b3528318b2025-08-20T02:18:21ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-03-0116419210.3390/wevj16040192Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective FunctionDayeon Lee0Dong Sik Kim1Beom Jin Chung2Young Mo Chung3Department of Electronics Engineering, Hankuk University of Foreign Studies, Yongin-si 17035, Republic of KoreaDepartment of Electronics Engineering, Hankuk University of Foreign Studies, Yongin-si 17035, Republic of KoreaResearch Center for Electrical and Information Technology, Seoul National University of Science and Technology, Seoul 01811, Republic of KoreaDepartment of Electronics and Information Engineering, Hansung University, Seoul 02876, Republic of KoreaAs the adoption of electric vehicles (EVs) rapidly increases, the expansion of charging infrastructure has become a critical issue. Unlike internal combustion engine vehicles, EV charging is sensitive to factors such as the time and location for charging, depending on the charging speed and capacity of the battery. Therefore, recommending an appropriate charging station that comprehensively considers not only the user’s preference but also the charging time, waiting time, charging fee rates, and power supply status is crucial for the user’s convenience. Currently, charging station recommendation services suggest suitable charging stations near a designated location and provide information on charging capacity, fee rates, and availability of chargers. Furthermore, research is being conducted on EV charging station recommendations that take into account various charging environments, such as power grid and renewable energy conditions. To solve these optimization problems, a large amount of information about the user’s history and conditions is required. In this paper, we propose a real-time charging station recommendation method based on minimal and simple current information while driving to the destination. We first propose a preference objective function that considers the factors of distance, time, and fees, and then analyze the recommendation results based on both synthetic and real-world charging environments. We also observe the recommendation results for different combinations of the weights for these factors. If we set all the weights equally, we can obtain appropriate recommendations for charging stations that reflect driving distance, trip time, and charging fees in a balanced way. On the other hand, as the number of charging stations in a given area increases, it has been found that gradually increasing the weighting of charging fees is necessary to alleviate the phenomenon of rising fee rates and provide balanced recommendations.https://www.mdpi.com/2032-6653/16/4/192charging station recommendationdriving situationelectric vehicle (EV)preference objective function |
| spellingShingle | Dayeon Lee Dong Sik Kim Beom Jin Chung Young Mo Chung Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function World Electric Vehicle Journal charging station recommendation driving situation electric vehicle (EV) preference objective function |
| title | Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function |
| title_full | Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function |
| title_fullStr | Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function |
| title_full_unstemmed | Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function |
| title_short | Recommendation of Electric Vehicle Charging Stations in Driving Situations Based on a Preference Objective Function |
| title_sort | recommendation of electric vehicle charging stations in driving situations based on a preference objective function |
| topic | charging station recommendation driving situation electric vehicle (EV) preference objective function |
| url | https://www.mdpi.com/2032-6653/16/4/192 |
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