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Virtual Sensors for Emissions of a Diesel Engine Produced by Evolutionary System Identification

  • Stephan M. Winkler
  • Markus Hirsch
  • Michael Affenzeller
  • Luigi del Re
  • Stefan Wagner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5717)

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.

Keywords

Diesel Engine Virtual Sensor Engine Control Unit Particulate Matter Emission Genetic Programming Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Stephan M. Winkler
    • 1
  • Markus Hirsch
    • 2
  • Michael Affenzeller
    • 1
  • Luigi del Re
    • 3
  • Stefan Wagner
    • 1
  1. 1.Heuristic and Evolutionary Algorithms LaboratoryUpper Austria University of Applied Sciences, School of Informatics, Communications and MediaHagenbergAustria
  2. 2.Linz Center of MechatronicsLinzAustria
  3. 3.Institute for Design and Control of Mechatronical SystemsJohannes Kepler University LinzLinzAustria

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