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Dynamic Mapping of Diesel Engine through System Identification

In English

Författare

Summary, in English

From a control design point of view, modern diesel engines are dynamic, nonlinear, MIMO systems. This paper presents a method to find low-complexity black-box dynamic models suitable for model predictive control (MPC) of NOx and soot emissions based on on-line emissions measurements. A four-input-five-output representation of the engine is considered, with fuel injection timing, fuel injection duration, exhaust gas recirculation (EGR) and variable geometry turbo (VGT) valve positions as inputs, and indicated mean effective pressure, combustion phasing, peak pressure derivative, NOx emissions, and soot emissions as outputs. Experimental data were collected on a six-cylinder heavy-duty engine at 30 operating points. The identification procedure starts by identifying local linear models at each operating point. To reduce the number of dynamic models necessary to describe the engine dynamics, Wiener

models are introduced and a clustering algorithm is proposed. A resulting set of two to five dynamic models is shown to be able to predict all outputs at all operating points with good accuracy.

Publiceringsår

2010

Språk

Engelska

Sidor

3015-3020

Publikation/Tidskrift/Serie

American Control Conference. Proceedings

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Other Mechanical Engineering
  • Control Engineering

Nyckelord

  • Diesel engines
  • System identification
  • Wiener models

Conference name

American Control Conference, 2010

Conference date

2010-06-30 - 2010-07-02

Conference place

Baltimore, MD, United States

Status

Published

Projekt

  • Diesel HCCI in a Multi-Cylinder Engine

Forskningsgrupp

  • LCCC

ISBN/ISSN/Övrigt

  • ISSN: 0743-1619
  • ISSN: 2378-5861
  • ISBN: 978-1-4244-7427-1
  • ISBN: 978-1-4244-7426-4