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  • 标题:Quantifying Performance of a Connected Vehicle by Optimal Control ∗
  • 本地全文:下载
  • 作者:Hyeongjun Park ; Rohit Gupta ; Edward Dai
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:15
  • 页码:328-334
  • DOI:10.1016/j.ifacol.2015.10.047
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper we exploit trajectory optimization techniques to quantify acceleration performance improvements in an advanced powertrain that are achievable if a preview of a launch event is available about 1 sec in advance through vehicle to traffic light communications. The vehicle is at idle immediately before acceleration. Based on the preview information, the idle speed is increased immediately before launch. A dynamic optimization approach is employed to optimize the idle speed set-point and trajectories of clutch and engine actuators after start of the acceleration. The optimization is applied to a high complexity model of powertrain. To perform the optimization, the trajectories being optimized are first transcribed using Gaussian kernel functions and then a mesh adaptive direct search (MADS) algorithm is applied. The achievable average acceleration with and without preview (i.e., without raising pre-launch engine speed) and for different sets of actuator trajectories being optimized under drivability constraints are compared thereby quantifying the benefits of vehicle-to-infrastructure connectivity.
  • 关键词:KeywordsPowertrain controloptimal controlintegrated powertrain controlacceleration performance optimizationconnected vehiclestrajectory optimization
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