{"title":"Battery and energy management in fleets of switchable battery EVs","authors":"Vladimir Zdornov, Y. Birk","doi":"10.1109/ISGTEurope.2011.6162632","DOIUrl":null,"url":null,"abstract":"This paper addresses the challenge of managing battery switching and charging in fleets of switchable battery electric vehicles (SBEVs). The goal of efficient management is to optimize resource utilization by the fleet, and thus the operational costs, under restricted power supply during operation hours. The resources include spare batteries, battery switching mechanisms, sophisticated infrastructure, as well as the availaibility of the charging power from the grid. We analyze performance limiting factors and formulate heuristic algorithms to tackle them. Furthermore, we evaluate the algorithms in simulations based on a synthetic travel schedule and energy demand model. The collected results expose interesting trade-offs between different resources that should be taken into account when designing the fleet's depot.","PeriodicalId":419250,"journal":{"name":"2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2011.6162632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper addresses the challenge of managing battery switching and charging in fleets of switchable battery electric vehicles (SBEVs). The goal of efficient management is to optimize resource utilization by the fleet, and thus the operational costs, under restricted power supply during operation hours. The resources include spare batteries, battery switching mechanisms, sophisticated infrastructure, as well as the availaibility of the charging power from the grid. We analyze performance limiting factors and formulate heuristic algorithms to tackle them. Furthermore, we evaluate the algorithms in simulations based on a synthetic travel schedule and energy demand model. The collected results expose interesting trade-offs between different resources that should be taken into account when designing the fleet's depot.