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  • 标题:BEV Remaining Range Estimation Based on Modern Control Theory - Initial Study
  • 本地全文:下载
  • 作者:Jan Dedek ; Tomas Docekal ; Stepan Ozana
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2019
  • 卷号:52
  • 期号:27
  • 页码:86-91
  • DOI:10.1016/j.ifacol.2019.12.738
  • 语种:English
  • 出版社:Elsevier
  • 摘要:The aim of this paper is to analyze the nature of algorithms for calculation of the range of battery electric vehicles (BEV) and to suggest possibilities of improvements of the current state in this field. Most of contemporary BEVs use inaccurate algorithms that probably do not take into account the planned route, but only the consumption history of the last few tens of kilometers. This regression analysis does not fulfill the sufficient quality for a reliable prediction of the exact range. Based on these erroneous predictions, the inexperienced BEV driver does not arrive at the planned destination and has to deal with the towing of the vehicle. This problem, along with the phenomenon called ”range anxiety” is one of the great negatives that hamper the mass expansion of BEV. While increasing the range is usually a question of increasing the battery capacity and thus the BEV price, deployment of accurate algorithms may not impact the overall cost of the vehicle and therefore has the potential to increase BEV’s popularity. This paper gives a description of the origin of the problem and motivation for its solution, then the specific methods that were created to identify the algorithms used by the most widespread cheap electric vehicles. The paper concludes with the discussion and evaluation of the results together with the possibilities of further research.
  • 关键词:KeywordsBattery electric vehicleRange anxietyRange estimationNissan LeafPeugeot IoN
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