Abstract
In this paper we discuss the generation of models for emissions of a Diesel engine, produced by genetic programming based evolutionary system identification: Models for the formation of NO x and particulate matter emissions are identified and analyzed. We compare these models to models designed by experts applying variables section and the identification of local polynomial models; analyzing the results summarized in the empirical part of this paper we see that the use of enhanced genetic programming yields models for emissions that are valid not only in certain parts of the parameter space but can be used as global virtual sensors.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Affenzeller, M., Wagner, S., Winkler, S.: Goal-oriented preservation of essential genetic information by offspring selection. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2005, vol. 2, pp. 1595–1596. Association for Computing Machinery (ACM), New York (2005)
Affenzeller, M., Winkler, S., Wagner, S., Beham, A.: Genetic Algorithms and Genetic Programming – Modern Concepts and Practical Applications. Chapman & Hall/CRC (2008)
Hirsch, M., Alberer, D., del Re, L.: Grey-box control oriented emissions models. In: Proceedings of IFAC World Congress 2008, pp. 8514–8519 (2008)
Hirsch, M., del Re, L.: Adaped D-optimal experimental design for transient emission models of diesel engines. In: Proceedings of SAE Congress 2009 (2009)
Langdon, W.B., Poli, R.: Foundations of Genetic Programming. Springer, Heidelberg (2002)
Ljung, L.: System Identification – Theory For the User, 2nd edn. PTR Prentice Hall, Upper Saddle River (1999)
Wagner, S.: Heuristic Optimization Software Systems – Modeling of Heuristic Optimization Algorithms in the HeuristicLab Software Environment. PhD thesis, Johannes Kepler University Linz (2009)
Warnatz, J., Maas, U., Dibble, R.W.: Combustion - Physical and Chemical Fundamentals, Modeling and Simulation, Experiments, Pollutant Formation. Springer, Heidelberg (1996)
Winkler, S.: Evolutionary System Identification - Modern Concepts and Practical Applications. PhD thesis, Johannes Kepler University Linz (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Winkler, S.M., Hirsch, M., Affenzeller, M., del Re, L., Wagner, S. (2009). Virtual Sensors for Emissions of a Diesel Engine Produced by Evolutionary System Identification. In: Moreno-DÃaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2009. EUROCAST 2009. Lecture Notes in Computer Science, vol 5717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04772-5_85
Download citation
DOI: https://doi.org/10.1007/978-3-642-04772-5_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04771-8
Online ISBN: 978-3-642-04772-5
eBook Packages: Computer ScienceComputer Science (R0)