Modeling and Model Reduction in Automotive Systems
(2006) In Research Reports TFRT-3242- Abstract
- The current control design development process in automotive industry and elsewhere involves many expensive experiments and hand-tuning of control parameters. Model based control design is a promising approach to reduce costs and development time. In this process low complexity models are essential. This thesis combines the areas of modeling and model reduction in automotive systems. A model of the exhaust gas oxygen sensor, used for air-fuel ratio control in automotive spark ignition engines, is developed and successfully validated. A model reduction case study is also performed on an engine air path. The heuristic method commonly used when modeling engine dynamics is compared with a more systematic approach based on the balanced... (More)
- The current control design development process in automotive industry and elsewhere involves many expensive experiments and hand-tuning of control parameters. Model based control design is a promising approach to reduce costs and development time. In this process low complexity models are essential. This thesis combines the areas of modeling and model reduction in automotive systems. A model of the exhaust gas oxygen sensor, used for air-fuel ratio control in automotive spark ignition engines, is developed and successfully validated. A model reduction case study is also performed on an engine air path. The heuristic method commonly used when modeling engine dynamics is compared with a more systematic approach based on the balanced truncation method. Finally, a method for model reduction of nonlinear systems has been derived. The procedure is focused on reducing the number of states using information obtained by linearization around trajectories. The methodology is closely tied to existing theory on error bounds and good results are shown in form of examples and simulation data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1023094
- author
- Nilsson, Oskar LU
- supervisor
-
- Anders Rantzer LU
- Rolf Johansson LU
- organization
- publishing date
- 2006
- type
- Thesis
- publication status
- published
- subject
- keywords
- Automotive systems, Lambda sensor, Model reduction, Modeling, Engine air path
- in
- Research Reports TFRT-3242
- pages
- 76 pages
- publisher
- Department of Automatic Control, Lund Institute of Technology, Lund University
- ISSN
- 0280-5316
- language
- English
- LU publication?
- yes
- id
- 6f98f0e5-3d0e-4b96-aeb1-835a7dc6f757 (old id 1023094)
- date added to LUP
- 2016-04-01 16:59:33
- date last changed
- 2018-11-21 20:45:46
@misc{6f98f0e5-3d0e-4b96-aeb1-835a7dc6f757, abstract = {{The current control design development process in automotive industry and elsewhere involves many expensive experiments and hand-tuning of control parameters. Model based control design is a promising approach to reduce costs and development time. In this process low complexity models are essential. This thesis combines the areas of modeling and model reduction in automotive systems. A model of the exhaust gas oxygen sensor, used for air-fuel ratio control in automotive spark ignition engines, is developed and successfully validated. A model reduction case study is also performed on an engine air path. The heuristic method commonly used when modeling engine dynamics is compared with a more systematic approach based on the balanced truncation method. Finally, a method for model reduction of nonlinear systems has been derived. The procedure is focused on reducing the number of states using information obtained by linearization around trajectories. The methodology is closely tied to existing theory on error bounds and good results are shown in form of examples and simulation data.}}, author = {{Nilsson, Oskar}}, issn = {{0280-5316}}, keywords = {{Automotive systems; Lambda sensor; Model reduction; Modeling; Engine air path}}, language = {{eng}}, note = {{Licentiate Thesis}}, publisher = {{Department of Automatic Control, Lund Institute of Technology, Lund University}}, series = {{Research Reports TFRT-3242}}, title = {{Modeling and Model Reduction in Automotive Systems}}, url = {{https://lup.lub.lu.se/search/files/4840270/8840423.pdf}}, year = {{2006}}, }