{"title":"Battery-aware energy-optimal Electric Vehicle driving management","authors":"K. Vatanparvar, Jiang Wan, M. A. Faruque","doi":"10.1109/ISLPED.2015.7273539","DOIUrl":null,"url":null,"abstract":"Recently, Electric Vehicles (EVs) have been considered as new paradigm of transportation in order to solve environmental concerns, e.g. air pollution. However, EVs pose new challenges regarding their Battery LifeTime (BLT), energy consumption, and energy costs related to battery charging. The EV power consumption may be estimated by having the route information and the EV specifications. Also, by having the battery characteristics, the battery capacity consumption and the BLT may be estimated for each route. In this paper, we propose a driving management which uses the above-mentioned information in order to optimize the driving route by being aware of the EV energy consumption, energy cost, and BLT. Our proposed driving management extends the BLT by 16.8% and reduces the energy consumption by 11.9% and energy cost by 12.6% on average, by selecting the optimized route instead of the fastest route.","PeriodicalId":421236,"journal":{"name":"2015 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISLPED.2015.7273539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
Recently, Electric Vehicles (EVs) have been considered as new paradigm of transportation in order to solve environmental concerns, e.g. air pollution. However, EVs pose new challenges regarding their Battery LifeTime (BLT), energy consumption, and energy costs related to battery charging. The EV power consumption may be estimated by having the route information and the EV specifications. Also, by having the battery characteristics, the battery capacity consumption and the BLT may be estimated for each route. In this paper, we propose a driving management which uses the above-mentioned information in order to optimize the driving route by being aware of the EV energy consumption, energy cost, and BLT. Our proposed driving management extends the BLT by 16.8% and reduces the energy consumption by 11.9% and energy cost by 12.6% on average, by selecting the optimized route instead of the fastest route.