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  • 标题:On quantifying the utility of look-ahead data for energy management
  • 本地全文:下载
  • 作者:Bharatkumar Hegde ; Avinash Vallur Rajendran ; Qadeer Ahmed
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:31
  • 页码:57-62
  • DOI:10.1016/j.ifacol.2018.10.011
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractConnectivity and technology integration focused on autonomy and safety in vehicles have equipped many vehicles with a host of sensors. Some of these sensors have the potential to aid energy management strategies by providing useful look-ahead data. Road features like speed limits, road grade, traffic sign locations etc. make up the look-ahead data for energy management. In this paper we quantify the utility of the look-ahead data in fuel economy improvements. The traffic-powertrain co-simulator provides the simulation framework necessary for our analysis. The methodology includes a look-ahead data based velocity predictor and an MPC based look-ahead controller to determine the fuel economy improvement with each look-ahead data. The results of the analysis indicate the existence of a Pareto front for fuel economy improvements with increased look-ahead data.
  • 关键词:Keywordslook aheadenergy managementhybrid vehicletraffic simulationco-simulationSUMOSimulink
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