{"title":"Comparative Study of Electric Vehicle Energy Consumption between Trunk Roads and Highways","authors":"Salima El Amrani, Mohammed Chennani, D. Belkhayat","doi":"10.1109/IRSEC48032.2019.9078169","DOIUrl":null,"url":null,"abstract":"The transportation field is one of the most important in energy consumption and it must move towards more sustainable development. Indeed, global warming is a reality and air pollution is worrying especially in large cities. In addition, the depletion of fossil resources is looming. Electric vehicles (EVs) are currently considered as the promising solution for reducing the dependence of transport on fossil fuels. Nevertheless, the overall adoption of these vehicles is disturbed by range limits of EVs. Therefore, it is necessary to predict the required power to drive and plan for charging whenever needed. The aim of this paper is to introduce a software tool permitting to predict and estimate energy consumption for any desired road. The software tool is based on mathematical model of the EV, which relates the energy to different factors such as the velocity, the acceleration and the road slope. In other side, this paper presents a comparative study between the highways and the trunk roads. The road chosen is Marrakech to Casablanca based on two different driving cycles, each one corresponding to a specific road. This method can be used for any EV, which the characteristics are known. Using the proposed model, the results show that EVs are more efficient in trunk roads than highways taking into account the energy recovery during the frequent braking.","PeriodicalId":6671,"journal":{"name":"2019 7th International Renewable and Sustainable Energy Conference (IRSEC)","volume":"46 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Renewable and Sustainable Energy Conference (IRSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRSEC48032.2019.9078169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The transportation field is one of the most important in energy consumption and it must move towards more sustainable development. Indeed, global warming is a reality and air pollution is worrying especially in large cities. In addition, the depletion of fossil resources is looming. Electric vehicles (EVs) are currently considered as the promising solution for reducing the dependence of transport on fossil fuels. Nevertheless, the overall adoption of these vehicles is disturbed by range limits of EVs. Therefore, it is necessary to predict the required power to drive and plan for charging whenever needed. The aim of this paper is to introduce a software tool permitting to predict and estimate energy consumption for any desired road. The software tool is based on mathematical model of the EV, which relates the energy to different factors such as the velocity, the acceleration and the road slope. In other side, this paper presents a comparative study between the highways and the trunk roads. The road chosen is Marrakech to Casablanca based on two different driving cycles, each one corresponding to a specific road. This method can be used for any EV, which the characteristics are known. Using the proposed model, the results show that EVs are more efficient in trunk roads than highways taking into account the energy recovery during the frequent braking.