New Engine Simulation Structure Model Applied to SI Engine

  • Mohammad Javad Nekooei Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, Malaysia.
  • Jaswar Koto Ocean & Aerospace Research Institute, Indonesia

Abstract

High  ratio  emissions  that  outcome  from  incomplete  combustion cause  air  contamination,  poorer  the  performance  of  the  spark ignition  (SI)  engine  and  raise  fuel  consumption.  Uncompleted combustion emitted a high ratio of CO, HC, NOx and PM harmful emissions such as come into atmosphere. This study has reviewed existing engine simulation structures using different methods as s as follows Neural Networks (NN), Sliding Mode Control (SMC), Proportional-Integral (PI) Predictive Control (MPC) and DRNN- based MPC method. The existing engine models were compared with  the  new  engine  simulation  structure  model  which  was proposed  by  the  authors,  using  Hybrid  Fuzzy  Logic  Control (HFLC) method in term of AFR.  The simulation engine model in Matlab/Simulink  using  new  engine  simulation  has  founded  that AFR  (15.02,  14.4)  which  closes  to  the  stoichiometric  value  of 14.7 compared by using Neural Networks (NN) method, a Sliding Mode  Control  (SMC)  method,  a  Proportional' Integral  (PI) control  method,  Model  Predictive  Control  (MPC)  method  and DRNN-based MPC method.

##Keywords:## New Engine Simulation Structure, SI Engine; Structure Model; Emission
Published
Apr 30, 2017
How to Cite
NEKOOEI, Mohammad Javad; KOTO, Jaswar. New Engine Simulation Structure Model Applied to SI Engine. Journal of Ocean, Mechanical and Aerospace -science and engineering-, [S.l.], v. 42, n. 1, p. 1-18, apr. 2017. ISSN 2527-6085. Available at: <https://isomase.org/Journals/index.php/jomase/article/view/185>. Date accessed: 25 apr. 2026. doi: http://dx.doi.org/10.36842/jomase.v42i1.185.

References

1 .Ahmed, Q. and Bhatti, A. I, 2011, Estimating SI engine efficiencies and parameters in second-order sliding modes. Industrial Electronics, IEEE Transactions on, 58, 4837-4846.
2. Alippi, C., De Russis, C. and Piuri, V, 1988, A fine control of the air-to-fuel ratio with recurrent neural networks. Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE, 1998. IEEE, 924-929.
3. Alippi, C., De Russis, C. and Piuri, V, 2003, A Neural-Network Based Control Solution to Air-Fuel Ratio Control for Automotive, IEEE Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 33, No. 2, May 2003.
4. Andersson, P, 2005, Air charge estimation in turbocharged spark ignition engines, Department of Electrical ngineering, Linköping University.
5. Balluchi, A., Benvenuti, L., Di Benedetto, M., Cardellino, S., Rossi, C. and Sangiovanni-Vincentelli, A, 1999, Hybrid control of the air-fuel ratio in force transients for multi-point injection engines. Decision and Control, 1999. Proceedings of the 38th IEEE Conference on, 1999. IEEE, 316-321.
6. Benninger, N.F. and Plapp, G. 1991, Requirements and Performance of Engine Management Systems under Transient Conditions. SAE Paper 910083.
7. Bosch, 1994, Automotive Electric/Electronic Systems. Wallendale, PA: Society of Automotive Engineers, 1994.
8. Cassidy Jr, J. F., Athans, M. and Lee, W. H, 1980, On the design of electronic automotive engine controls using linear quadratic control theory, Automatic Control, IEEE Transactions on, 25, 901-912.
9. Ceviz, M, 2007, Intake plenum volume and its influence on the engine performance, cyclic variability and emissions, Energy Conversion and Management, 48, 961-966.
10. Ceviz, M. and Ak?n, M, 2010, Design of a new SI engine intake manifold with variable length plenum, Energy Conversion and Management, 51, 2239-2244.
11. Chang, C.-F., Fekete, N. P. and Powell, J. D, 1993, Engine air-fuel ratio control using an event-based observer. SAE Technical Paper.
12. Chang, C.-F., Fekete, N. P., Amstutz, A. and Powell, J. D, 1995, Air-fuel ratio control in spark-ignition engines using estimation theory. Control Systems Technology, IEEE Transactions on, 3, 22-31.
13. Cook, J. and Powell, B. K, 1988, Modeling of an internal combustion engine for control analysis. Control Systems Magazine, IEEE, 8, 20-26.
14. Ebrahimi, B., Tafreshi, R., Masudi, H., Franchek, M., Mohammadpour, J. and Grigoriadis, K, 2012, A parameter-varying filtered PID strategy for air–fuel ratio control of spark ignition engines, Control Engineering Practice, 20, 805-815.
15. Gnanam, G., Sobiesiak, A., Reader, G., & Zhang, C, 2006, An HCCI engine fuelled with iso-octane and ethanol (No. 2006-01-3246). SAE Technical Paper.
16. Hashimoto, S., Okuda, H., Okada, Y., Adachi, S., Niwa, S. and Kajitani, M, 2006, An engine control systems design for low emission vehicles by generalized predictive control based on identified model, Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE, 2006. IEEE, 2411-2416.
17. Hendricks, E. and Sorenson, S. C, 1991, SI engine controls and mean value engine modelling. SAE Technical paper. 18.Hendricks, E., Chevalier, A., Jensen, A., Sorenson, S.C., 1996. Modelling of the intake manifold filling dynamics. SAE paper 960037.
19. Heywood, J. B, 1988, Internal combustion engine fundamentals, Mcgraw-hill New York.
20. Koto, J. and Ikeda, Y. (2002). A Feasibility Study on a Podded Propulsion LNG Tanker in Arun, Indonesia–Osaka, Japan Route. The Twelfth International Offshore and Polar Engineering Conference, 2002. International Society of Offshore and Polar Engineers, pp 525 ~ 532.
21. Manzie, C., Palaniswami, M., & Watson, H. (2001). Gaussian networks for fuel injection control. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 215(10), 1053-1068.
22. Mohammad Javad Nekooei, J. Koto, M.Pauzi Ghani and Zahra Dehghani, 2015, A New Engine Simulation Structure Model Applied to SI Engine Controlling, Journal of Ocean, Mechanical and Aerospace -science and engineering-,Vol.22, pp.9-12.
23. Mohammad Javad Nekooei, Jaswar Koto, 2017, Hybrid Fuzzy Logic Controller in Matlab/Simulink for Controlling AFR of SI Engine, International Journal of Environmental Research & Clean Energy, Vol.5 (1), pp.11-20, January, 2017.
24. Mohammad Javad Nekooei, Jaswar, Agoes Priyanto and Zahra Dehghani, 2013, A Review on Engine MVEM Models and AFR Control Methods to Developing a New Engine Model and Ziegler Nichols PID Fuzzy controller: Applied to SI Engines, Journal of Applied Sciences Research, 9(13): pages 6710-6725.
25. Mohammad Javad Nekooei, Jaswar, Agoes Priyanto, Zahra Dehghani, 2014, A Study on Combustion Modelling of Marine Engines Concerning the Cylindrical Pressure, Journal of Applied Science and Agriculture, 9(8) June 2014, Pages: 39-44.
26. Müller, M., Hendricks, E. and Sorenson, S. C, 1998, Mean value modelling of turbocharged spark ignition engines. SAE Technical Paper.
27. Nekooei, Mohammad Javad, Jaswar Koto, A.Priyanto, Zahra Dehghani, 2015, Reviewed on Combustion Modelling of Marine Spark-Ignition Engines, Journal of Ocean, Mechanical and Aerospace -Science and Engineering-,Vol.17 1 (2015): 1-4.
28. Nekooei, Mohammad Javad, Jaswar Koto, and A. Priyanto, 2014, Review on Combustion Control of Marine Engine by Fuzzy Logic Control Concerning the Air to Fuel Ratio, Jurnal Teknologi 66.2.
29. Nekooei, Mohammad Javad, Jaswar Koto, and A. Priyanto, 2015, A Simple Fuzzy Logic Diagnosis System for Control of Internal Combustion Engines, Jurnal Teknologi 74.5 (2015).
30. Nekooei, Mohammad Javad, Jaswar Koto, and Agoes Priyanto, 2013. Designing Fuzzy Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control: Applied to Internal Combustion Engine, Applied Mechanics and Materials. Vol. 376. 2013.
31. Pieper, J. and Mehrotra, R, 1999, Air/fuel ratio control using sliding mode methods. American Control Conference, 1999. Proceedings of the 1999, 1999. IEEE, 1027-1031.
32. Priyanto, Agoes, and Mohammad Javad Nekooei, JaswarKoto, 2014, Design Online Artificial Gain Updating Sliding Mode Algorithm: Applied to Internal Combustion Engine, Applied Mechanics and Materials. Vol. 493. 2014.