This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Development of recurrent neural networks for virtual sensing of NOx emissions in internal combustion engines

Journal Article
ISSN: 1946-3952, e-ISSN: 1946-3960
Published September 13, 2009 by Consiglio Nazionale delle Ricerche in Italy
Development of recurrent neural networks for virtual sensing of NOx emissions in internal combustion engines
Citation: Arsie, I., Pianese, C., and Sorrentino, M., "Development of recurrent neural networks for virtual sensing of NOx emissions in internal combustion engines," SAE Int. J. Fuels Lubr. 2(2):354-361, 2010,
Language: English


  1. Alberer D. del Re K. Winkler S. Langthaler P. 2005 Virtual Sensor Design of Particulate and Nitric Oxide Emissions in a DI Diesel Engine SAE paper 2005-24-063
  2. Arsie I. Pianese C. Rizzo G. 1998 Models for the Prediction of Performance and Emissions in a Spark Ignition Engine - A Sequentially Structured Approach SAE Paper 980779 , SAE 1998 Transactions - Journal of Engines Vol. 106 1065 1079
  3. Arsie I. Pianese C. Sorrentino M. 2002 Recurrent Neural Network Based Air-Fuel Ratio Observer for SI Internal Combustion Engines 6 th ASME Biennial Conference on Engineering Systems Design and Analysis Istanbul, Turkey July 8–11 2002
  4. Arsie, I. Pianese, C. Sorrentino, M. “Development and Real-Time Implementation of Recurrent Neural Networks for AFR Prediction and Control,” SAE Int. J. Passeng. Cars – Mech. Syst. 1 1 403 412 2008
  5. Arsie, I. Pianese, C. Sorrentino, M. 2006 A procedure to enhance identification of recurrent neural networks for simulating air-fuel ratio dynamics in SI engines Engineering Applications of Artificial Intelligence vol. 19 1 65 77
  6. Atkinson C. M. Long T. W. Hanzevack E. L. 1998 Virtual Sensing: A Neural Network-based Intelligent Performance and Emissions Prediction System for On-Board Diagnostics and Engine Control SAE paper 980516
  7. Ayeb M. Theuerkauf H. J. Winsel T. 2005 SI Engine Emissions Model Based on Dynamic Neural Networks and D-Optimality SAE paper 2005-01-0019
  8. Brand D. Onder C. Guzzella L. 2007 Virtual NO Sensor for Spark-Ignition Engines Int. J. Engine Res. Vol. 8
  9. Goodwin G. C. 1999 Evaluating the Performance of Virtual Sensors 1999 IEEE Conference on Information, Decision and Control 8–10 Feb. 1999 5 12
  10. Haykin, S. 1999 Neural Networks Prentice Hall
  11. Heywood J. B. 1988 Internal Combustion Engine Fundamentals MC Graw Hill
  12. Inagaki H Ohata A Inoue T 1990 An Adaptive Fuel Injection Control with Internal Model in Automotive Engines, IECON '90 16 th Annual Conference of IEEE 78 83
  13. Kolmogorov A. N. 1965 On the Representation of Continuous Functions of Many Variables by Superposition of Continuous Functions of One Variable and Addition, Amer Math. Society Translations 28 55 59 1965
  14. Miller R. Davis G. Lavoie G. Newman C. Gardner T. 1998 A Super-Extended Zel'dovich Mechanism for NOx Modeling and Engine Calibration SAE paper 980781
  15. Nørgaard, M. Ravn, O. Poulsen, N. L. Hansen, L. K. 2000 Neural Networks for Modelling and Control of Dynamic Systems Springer-Verlag
  16. Patterson, D. W. 1995 Artificial Neural Networks - Theory and Applications Prentice Hall
  17. Ramos J. I. 1989 Internal Combustion Engine Modeling Hemisphere Publishing Corporation
  18. Sevilla J. Pulido C. 1998 Virtual Industrial Sensors Trough Neural Networks. Demonstration Examples in Nuclear Power Plants Proceedings of the 1998 IEEE Conference on Instrumentation and Measurement Technology Volume 1 293 297 18–21 May 1998 St. Paul, MN, USA
  19. Subramaniam M. N. Tomazic D. Tatur M. Laermann M. 2008 An Artificial Neural Network-based Approach for Virtual NOx Sensing SAE Paper 2008-01-0753

Cited By