Abstract
The Engine Management System is the system responsible for controlling the combustion in an automotive engine that is a very complex system with various sensors and actuators involved. This paper presents the use of artificial neural networks to estimate values of the oxygen sensor, which is one of the main sensors used by the Engine Management System and is directly related to the control of combustion and emissions. Together with the costs reduction, the control of emissions has received great focus by the automotive industry, where one of the reasons is actually the environmental issue.
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.
References
ANFAVEA, 2008, “Brazilian auto industry yearbook – 2008,” in portuguese, Brazilian automakers association, São Paulo, 2008.
R. J. Howlett, “Monitoring and control of an internal combustion engine air-fuel Ratio using Neural and Fuzzy Techniques,” Department of Electrical and Electronic Engineering, University of Brighton, UK, 1998.
P. Amato, N. Cesario, M. Di Meglio and F. Pirozzi, “Realization of a virtual lambda sensor on a fixed precision system,” Proceedings of the Design, Automation and Test in Europe, IEEE, vol. 3, p. 192-197, 2005.
S. Kamat, V. Diwanji, J. Smith, H. Javaherian and K. P. Madhavan, “Virtual sensing of SI engines using recurrent neural networks,” 2006 SAE World Congress, Electronic Engine Controls, SAE, 2006
S. Haykin, “Neural networks,” Prentice-Hall, 1999.
Z. L. Kovács, “Artificial neural networks: concepts and applications,” in portuguese, Edição Acadêmica, São Paulo, 1996.
R. M. Golden, “Mathematical methods for neural network analysis and design,” MIT Press, 1996.
DELPHI, “A model-based environment for production engine management system (EMS) development,” SAE, 2001.
BOSCH, “Automotive technology handbook,” in portuguese, Edgard Blucher, São Paulo, 2005.
DELPHI., “Planar oxygen sensor: application manual.,” Delphi Automotive Systems, Piracicaba, 2005.
BOSCH, “Gasoline-engine management,” SAE, 1999.
DELPHI, “Delphi high function engine management system,” Delphi Automotive Systems, Troy, 2006.
BRASIL, Resolution number 18, May 6th, 1986. “Air pollution control program for auto vehicles – PROCONVE,” Union Official Daily, Brasília, 1986.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media B.V.
About this paper
Cite this paper
Richter, T., Oliveira, A.F., da Silva, I.N. (2010). Virtual Oxygen Sensor Implementation Using Artificial Neural Networks. In: Iskander, M., Kapila, V., Karim, M. (eds) Technological Developments in Education and Automation. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3656-8_41
Download citation
DOI: https://doi.org/10.1007/978-90-481-3656-8_41
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-3655-1
Online ISBN: 978-90-481-3656-8
eBook Packages: Humanities, Social Sciences and LawEducation (R0)