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A model reduction case study: automotive engine air path

Nilsson, Oskar LU ; Rantzer, Anders LU and Chauvin, J (2006) 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control p.851-856
Abstract
Low complexity plant models are essential for model based control design. Often a detailed high order model is available and simplification to a low order approximative model is needed. This paper presents a case study of two model reduction methodologies applied on the automotive engine air path. The first methodology is based on balanced truncation of models obtained by linearization around equilibria and trajectories. Under appropriate assumptions, this technique yields strict bounds on the approximation error. The second is a heuristic methodology, based on intuition commonly used when modeling engine dynamics. Although it is successfully used in practice, the approximation error is seldom known. The two methodologies are used to... (More)
Low complexity plant models are essential for model based control design. Often a detailed high order model is available and simplification to a low order approximative model is needed. This paper presents a case study of two model reduction methodologies applied on the automotive engine air path. The first methodology is based on balanced truncation of models obtained by linearization around equilibria and trajectories. Under appropriate assumptions, this technique yields strict bounds on the approximation error. The second is a heuristic methodology, based on intuition commonly used when modeling engine dynamics. Although it is successfully used in practice, the approximation error is seldom known. The two methodologies are used to derive simple models for the required fuel charge in an SI engine, given engine speed and throttle positions. Performance, complexity and similarities of the two resulting low order models are compared (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
throttle position, engine dynamics, intuition, heuristic methodology, approximation error, linearization, model based control design, model reduction, automotive engine air path, engine speed, spark ignition engine, fuel charge
in
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
pages
6 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
external identifiers
  • WOS:000245233801051
  • Scopus:43049165463
ISBN
0-7803-9797-5
DOI
10.1109/CCA.2006.286062
language
English
LU publication?
yes
id
45ea212c-ba99-4497-bf0f-fee87588df62 (old id 617112)
date added to LUP
2007-11-24 12:04:05
date last changed
2017-01-01 08:01:20
@inproceedings{45ea212c-ba99-4497-bf0f-fee87588df62,
  abstract     = {Low complexity plant models are essential for model based control design. Often a detailed high order model is available and simplification to a low order approximative model is needed. This paper presents a case study of two model reduction methodologies applied on the automotive engine air path. The first methodology is based on balanced truncation of models obtained by linearization around equilibria and trajectories. Under appropriate assumptions, this technique yields strict bounds on the approximation error. The second is a heuristic methodology, based on intuition commonly used when modeling engine dynamics. Although it is successfully used in practice, the approximation error is seldom known. The two methodologies are used to derive simple models for the required fuel charge in an SI engine, given engine speed and throttle positions. Performance, complexity and similarities of the two resulting low order models are compared},
  author       = {Nilsson, Oskar and Rantzer, Anders and Chauvin, J},
  booktitle    = {2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control},
  isbn         = {0-7803-9797-5},
  keyword      = {throttle position,engine dynamics,intuition,heuristic methodology,approximation error,linearization,model based control design,model reduction,automotive engine air path,engine speed,spark ignition engine,fuel charge},
  language     = {eng},
  pages        = {851--856},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {A model reduction case study: automotive engine air path},
  url          = {http://dx.doi.org/10.1109/CCA.2006.286062},
  year         = {2006},
}