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  • 标题:Identification of Control-Relevant Diesel Engine Models Using a Local Linear Parametric Approach * * This work was supported by DAF Trucks N.V.
  • 本地全文:下载
  • 作者:Thijs van Keulen ; Lars Huijben ; Tom Oomen
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:7836-7841
  • DOI:10.1016/j.ifacol.2017.08.1061
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractControl is essential to meet future emission requirements in combustion engines. Accurate models are required to design a controller that achieves robust performance over a range of operating conditions. The aim of this paper is to develop a non-parametric and parametric identification procedure that is specifically tailored towards high performance diesel engine control, while minimizing measurement time. First, a non-parametric identification is proposed where the inputs are excited with multisines. A Local Rational Method (LRM) is employed to obtain multivariable Frequency Response Functions (FRFs) in a single experiment. Secondly, a parametric identification procedure uses the non-parametric estimates to obtain control-relevant parametric models. The identification procedure is demonstrated using a modern Heavy-Duty Diesel (HDD) engine providing highly accurate low order parametric models for a 2x2 plant using just 300s of measurement time at an engine operating point.
  • 关键词:KeywordsEngine modellingcontrolAutomotive system identificationmodellingFrequency domain identificationIdentification for controlAutomotive sensorsactuators
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