Identification of control-relevant diesel engine models using a local linear parametric approach

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Abstract

Control 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.

Original languageEnglish
Pages (from-to)7836-7841
Number of pages6
JournalIFAC-PapersOnLine
Volume50
Issue number1
DOIs
Publication statusPublished - 1 Jul 2017
Event20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress) - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20
https://www.ifac2017.org/

Keywords

  • actuators
  • Automotive sensors
  • Automotive system identification
  • control
  • Engine modelling
  • Frequency domain identification
  • Identification for control
  • modelling

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