Planning an itinerary for an electric vehicle

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI:10.1109/ENERGYCON.2014.6850603

H. Chale-Gongora, Olivier de Weck, Abdelkrim Doufene, T. Ishimatsu, D. Krob

{"title":"Planning an itinerary for an electric vehicle","authors":"H. Chale-Gongora, Olivier de Weck, Abdelkrim Doufene, T. Ishimatsu, D. Krob","doi":"10.1109/ENERGYCON.2014.6850603","DOIUrl":null,"url":null,"abstract":"The steady increase in oil prices and awareness regarding environmental risks due to carbon dioxide emissions are promoting the current interest in electric vehicles. However, the current relatively low driving range (autonomy) of these vehicles, especially compared with the autonomy of existing internal combustion vehicles, remains an obstacle to their development. In order to reassure a driver of an electric vehicle and allow him to reach his destinations beyond the battery capacity, we describe a system which generates an energy plan for the driver. We present in this paper the electric vehicle ecosystem and we focus on the contribution of using the generalized multi-commodity network flow (GMCNF) model as a vehicle routing model that considers energy consumption and charging time in order to ensure the usage of an electric vehicle beyond its embedded autonomy by selecting the best routes to reach the destination with minimal time and/or cost. We also present some perspectives related to the utilization of autonomous electric vehicles and wireless charging systems. We conclude with some open research questions.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Energy Conference (ENERGYCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENERGYCON.2014.6850603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 16

Abstract

The steady increase in oil prices and awareness regarding environmental risks due to carbon dioxide emissions are promoting the current interest in electric vehicles. However, the current relatively low driving range (autonomy) of these vehicles, especially compared with the autonomy of existing internal combustion vehicles, remains an obstacle to their development. In order to reassure a driver of an electric vehicle and allow him to reach his destinations beyond the battery capacity, we describe a system which generates an energy plan for the driver. We present in this paper the electric vehicle ecosystem and we focus on the contribution of using the generalized multi-commodity network flow (GMCNF) model as a vehicle routing model that considers energy consumption and charging time in order to ensure the usage of an electric vehicle beyond its embedded autonomy by selecting the best routes to reach the destination with minimal time and/or cost. We also present some perspectives related to the utilization of autonomous electric vehicles and wireless charging systems. We conclude with some open research questions.

查看原文本刊更多论文

规划电动汽车的行程

油价的持续上涨和对二氧化碳排放带来的环境风险的认识正在推动人们对电动汽车的兴趣。然而，目前这些汽车的行驶里程(自主性)相对较低，特别是与现有内燃机汽车的自主性相比，仍然是阻碍其发展的障碍。为了让电动汽车的司机放心，并允许他在超出电池容量的情况下到达目的地，我们描述了一个为司机生成能量计划的系统。我们在本文中介绍了电动汽车生态系统，并将重点放在使用广义多商品网络流(GMCNF)模型作为车辆路由模型的贡献上，该模型考虑了能源消耗和充电时间，以便通过选择以最小时间和/或成本到达目的地的最佳路线来确保电动汽车的使用超出其嵌入式自主性。我们还提出了一些与自动驾驶电动汽车和无线充电系统的应用相关的观点。最后，我们提出一些开放性的研究问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2014 IEEE International Energy Conference (ENERGYCON)

自引率

0.00%

发文量