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
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:
https://lup.lub.lu.se/record/617112
- author
- Nilsson, Oskar
LU
; Rantzer, Anders
LU
and Chauvin, J
- organization
- publishing date
- 2006
- 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
- host publication
- 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
- conference location
- Munich, Germany
- conference dates
- 2006-10-04 - 2006-10-06
- 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
- 2016-04-04 11:04:14
- date last changed
- 2023-09-06 08:49:46
@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}},
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}},
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}},
doi = {{10.1109/CCA.2006.286062}},
year = {{2006}},
}