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Input and Structure Choices of Neural Networks on the Fuel Flow Rate Prediction in the Transient Operation Condition

Journal Article
2011-01-2458
ISSN: 1946-3936, e-ISSN: 1946-3944
DOI: https://doi.org/10.4271/2011-01-2458
Published November 01, 2012 by SAE International in United States
Input and Structure Choices of Neural Networks on the Fuel Flow Rate Prediction in the Transient Operation Condition
Sector:
Citation: Deng, J., Stobart, R., and Ordys, A., "Input and Structure Choices of Neural Networks on the Fuel Flow Rate Prediction in the Transient Operation Condition," SAE Int. J. Engines 5(4):1535-1550, 2012, https://doi.org/10.4271/2011-01-2458.
Language: English

References

  1. Ebner, H. Köck, K. “New Fuel Mass Flow Meter - A Modern and Reliable Approach to Continuous and Accurate Fuel Consumption Measurement,” SAE Technical Paper 2000-01-1330 2000 10.4271/2000-01-1330
  2. Ebner, H. Jaschek, A. “The Importance of Blow-By Measurements, Measuring Equipment Required and Implementation,” SAE Technical Paper 981081 1998 10.4271/981081
  3. Mohtasebi, S. Hong, H. “Low Cost Electronically Controlled Fuel Metering System for Small Gas Turbine Engines,” SAE Technical Paper 1999-01-0545 1999 10.4271/1999-01-0545
  4. Mohtasebi, S. Hong, H. Krepec, T. “New Electronic Controlled Continuous Flow Metering Systems for Automotive Applications” CSME Transactions 23 2 321 337 1999
  5. Wu, B. Prucka, R. Filipi, Z. Kramer, D. et al. “Cam-phasing Optimization Using Artificial Neural Networks as Surrogate Models-Fuel Consumption and NOx Emissions,” SAE Technical Paper 2006-01-1512 2006 10.4271/2006-01-1512
  6. Ghazikhani, M. Mirzaii, I. “Soot emission prediction of a waste-gated turbo-charged DI diesel engine using artificial neural network” Neural Computing and Applications 20 2 303 308 2011
  7. He, Y. Rutland, C.J. “Application of Artificial Neural Networks in Engine Modeling,” International Journal of Engine Research 5 4 281 296 2004
  8. Maass, B. Deng, J. Stobart, R. K. “Prediction of Smoke Emissions of a Heavy Duty Diesel Engine with a NLARX Model,” American Control Conference 2009
  9. Vance, J. Singh, A. Kaul, B. et. al. “Neural network controller development and implementation for spark ignition engines with high EGR levels” IEEE Transactions on Neural Networks 18 4 1083 1100 2007
  10. Bose, N. Kumar, N. S. “Prediction of Engine Emissions Through Fuzzy Logic Modelling,” International Conference on Computational Intelligence and Multimedia Applications 2007
  11. Bose, N. Kumar, N. “Prediction of emissions using combustion parameters in a diesel engine through fuzzy logic techniques” International Journal of Computational Intelligence and Applications 8 2 195 207 2009
  12. Schilling, A. Amstutz, A. Onder, C. H. Guzzella, L. “A real-Time Model for the Prediction of the NOx Emissions in DI Diesel Engines,” Proceedings of the IEEE International Conference on Control Applications Munich, Germany Oct. 2006
  13. Schilling, A. Amstutz, A. Onder, C. et, al. “A real-Time Model for the Prediction of the NOx Emissions in DI Diesel Engines,” Proceedings of the IEEE International Conference on Control Applications 2042 2047 2006
  14. Deng, J. Maass, B. Stobart, R. Winward, E. et al. “Accurate and Continuous Fuel Flow Rate Measurement Prediction for Real Time Application,” SAE Int. J. Engines 4 1 1724 1737 2011 10.4271/2011-01-1303
  15. Deng, A. Baass, B. Stobart “Particulate Matter Prediction of Both Steady-State and Transient Operation in Diesel Engines” Proceedings of the Institution of Mechanical Engineers, Part D, Journal of Automobile Engineering
  16. AVL 733S Operator Manual
  17. Maass, B. Stobart, R. Deng, J. “Diesel Engine Emissions Prediction Using Parallel Neural Networks,” American Control Conference 2009
  18. Haykin, S. “Neural Networks - A Comprehensive Foundation;” Prentice Hall Inc. Second 1999
  19. Polat, K. Gϋneş, S. A hybrid medical decision making system based on principal component analysis K-NN based weighted pre-processing and adaptive neuro-fuzzy inference system 2006 16 913 921
  20. Wang, X. Paliwal, K.K. Feature extraction dimensionality reduction algorithm and their applications in vowel recognition Journal of Pattern Recognition society 2003 36 10 2429 2439
  21. Maione, B. Lino, P. A. Rizzo, A. “Neural Network Nonlinear Modeling of a Common Rail Injection System for a CNG Engine” WSEAS Transactions on Systems 5 3 2164 2169 July 2004
  22. Seykens, X.L.J. Somers, L.M.T. Baert, R.S.G. “Detailed modelling of common rail fuel injection process, in. Mecca, Journal of Middle European Construction and Design of Cars” MECCA 3 30 39 2005
  23. Funahashi, K. “On the Approximate Realization of Continuous Mappings by Neural Networks,” Neural Networks 2 3 183 192 1989

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