A model reduction case study: automotive engine air path
Author
Summary, in English
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
Department/s
Publishing year
2006
Language
English
Pages
851-856
Publication/Series
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
Document type
Conference paper
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
Topic
- Control Engineering
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
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 date
2006-10-04 - 2006-10-06
Conference place
Munich, Germany
Status
Published
ISBN/ISSN/Other
- ISBN: 0-7803-9797-5