Anastasia Popiolek, P. Dessante, M. Petit, Z. Dimitrova, Mouhcine Waraq
{"title":"通过实时通信降低有限里程电动汽车的高速公路充电基础设施成本","authors":"Anastasia Popiolek, P. Dessante, M. Petit, Z. Dimitrova, Mouhcine Waraq","doi":"10.1109/ITEC55900.2023.10186939","DOIUrl":null,"url":null,"abstract":"Optimizing the charging service for long-distance trips with limited-range electric vehicles (EVs) is one of the significant challenges to EVs' adoption. Multiple approaches have been developed to optimize the charging infrastructure layout to capture EV flow or, on the contrary, to use the existing charging network more efficiently. In the present paper, we propose a new method that minimizes the infrastructure cost when the EV flow is, in addition, controlled by a charging strategy improving the charging station use rate. Each EV using the charging strategy minimizes its traveling time thanks to real-time communication between EVs and charging stations: the EVs share their intended charging plans, and the stations, the estimation of future waiting times. To show the gain in infrastructure cost provided by the communication, we compute, thanks to a Grey Wolf Optimizer, the optimal infrastructure layout for different fleets of limited-range EVs using real-time communication. The optimal layout obtained for each fleet is then compared to the optimal infrastructure we should build in cases where the EVs do not communicate. The communication strategy enables a reduction by at least 8.3% of the number of charging points and saves at least 7.3% of the infrastructure cost.","PeriodicalId":234784,"journal":{"name":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Highway charging infrastructure costs reduction for limited-range electric vehicles with real-time communication\",\"authors\":\"Anastasia Popiolek, P. Dessante, M. Petit, Z. Dimitrova, Mouhcine Waraq\",\"doi\":\"10.1109/ITEC55900.2023.10186939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimizing the charging service for long-distance trips with limited-range electric vehicles (EVs) is one of the significant challenges to EVs' adoption. Multiple approaches have been developed to optimize the charging infrastructure layout to capture EV flow or, on the contrary, to use the existing charging network more efficiently. In the present paper, we propose a new method that minimizes the infrastructure cost when the EV flow is, in addition, controlled by a charging strategy improving the charging station use rate. Each EV using the charging strategy minimizes its traveling time thanks to real-time communication between EVs and charging stations: the EVs share their intended charging plans, and the stations, the estimation of future waiting times. To show the gain in infrastructure cost provided by the communication, we compute, thanks to a Grey Wolf Optimizer, the optimal infrastructure layout for different fleets of limited-range EVs using real-time communication. The optimal layout obtained for each fleet is then compared to the optimal infrastructure we should build in cases where the EVs do not communicate. The communication strategy enables a reduction by at least 8.3% of the number of charging points and saves at least 7.3% of the infrastructure cost.\",\"PeriodicalId\":234784,\"journal\":{\"name\":\"2023 IEEE Transportation Electrification Conference & Expo (ITEC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Transportation Electrification Conference & Expo (ITEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITEC55900.2023.10186939\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Transportation Electrification Conference & Expo (ITEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITEC55900.2023.10186939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Highway charging infrastructure costs reduction for limited-range electric vehicles with real-time communication
Optimizing the charging service for long-distance trips with limited-range electric vehicles (EVs) is one of the significant challenges to EVs' adoption. Multiple approaches have been developed to optimize the charging infrastructure layout to capture EV flow or, on the contrary, to use the existing charging network more efficiently. In the present paper, we propose a new method that minimizes the infrastructure cost when the EV flow is, in addition, controlled by a charging strategy improving the charging station use rate. Each EV using the charging strategy minimizes its traveling time thanks to real-time communication between EVs and charging stations: the EVs share their intended charging plans, and the stations, the estimation of future waiting times. To show the gain in infrastructure cost provided by the communication, we compute, thanks to a Grey Wolf Optimizer, the optimal infrastructure layout for different fleets of limited-range EVs using real-time communication. The optimal layout obtained for each fleet is then compared to the optimal infrastructure we should build in cases where the EVs do not communicate. The communication strategy enables a reduction by at least 8.3% of the number of charging points and saves at least 7.3% of the infrastructure cost.