Review on Combustion Control of Marine Engine by Fuzzy Logic Control Concerning the Air to Fuel Ratio

Authors

  • Mohammad Javad Nekooei Department of Aeronautics, Automotive and Ocean Engineering , Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Jaswar Jaswar Department of Aeronautics, Automotive and Ocean Engineering , Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • A. Priyanto Department of Aeronautics, Automotive and Ocean Engineering , Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v66.2493

Keywords:

SI marine engine, air to fuel ratio, fuzzy logic control

Abstract

This research reviews a close loop control-oriented model, combined with air to fuel ratio, to regulate  combustion phasing in a spark- ignition marine engine operation. On the other hand ,Stoichiometric air-to-fuel ratio () control plays a significant role on the  three way catalysts in the reduction of exhaust pollutants of the SI marine engine. Air to fuel management for SI marine engines is a major challenge from the control point of view because of the highly nonlinear behavior of this system. For this reason, linear control techniques are unable to provide the required performance, and nonlinear controllers are used instead. Therefore, a fuzzy MIMO Control system is designed for robust control of  lambda. As an accurate and control oriented model, an  air to fuel ratio model of a Spark Ignition (SI) marine engine is developed to generate simulation data of the engine's subsystems. The Goal of this control is to maintain the A/F ratio at stoichiometry.

References

Air Pollution and Climate Secretariat, Air pollution from ships, http://www.airclim.org/air-pollution-ships.

Jaswar and Yoshiho Ikeda. 2002. A Feasibility Study on a Podded Propulsion LNG Tanker in Arun, Indonesia–Osaka, Japan Route, Proceedings of The Twelfth International Offshore and Polar Engineering Conference, Kitakyushu, Japan, May 26–31.

R. Antonić, A. Cibilić, I. Golub, Z. Kulenović, V. Tomas. 2011. Impact of the Environmental Sea Conditions to Ship’s Propulsion Engine Dynamics, Paper Presented at the 15th International Research/Expert Conference Trends In The Development Of Machinery And Associated Technology-TMT 2011.

Jaswar. 1996. Control Surface Design of Autonomous Underwater Vehicle, Research Project Report, Australian Engineering Maritime Comparative Research Center, Australia.

Hulda Winnes. 2010. Emissions of NOX and particles from manoeuvring ships, Transportation Research Part D-Transport and Environment. 15(4)s: 204–211.

C. Maftei, I. Moreira, C. G. 2009. Soares, Simulation of the Dynamics of a Marine Diesel Engine, Proceedings of IMarEST-Part A-Journal of Marine Engineering and Technology. 29–43.

M. Altosole and M. Figari. 2011. Effective Simple Methods for Numerical Modeling of Marine Engines in Ship Propulsion Control Systems Design. Journal of Naval Architecture and Marine Engineering. 8: 129–147.

O. Bondarenko, M. Kashiwagi, S. Naito. 2009. Dynamics of Diesel Engine in the Framework of Ship Propulsion Plant, Conference Proceedings, the Japan Society of Naval Architects and Ocean Engineers. 335–338.

B. Siciliano and O. Khatib. 2008. Springer Handbook of Robotics. Springer-Verlag New York Inc.

Boiko, et al. 2007. Analysis of Chattering in Systems with Second-order Sliding Modes. IEEE Transactions on Automatic Control. 52: 2085–2102.

B. Siciliano and O. Khatib. 2008. Springer Handbook of Robotics. Springer-Verlag New York Inc.

Xiao, Baitao, Ph.D. 2013. Adaptive model based combustion phasing control for multi fuel spark ignition engines. ProQuest® Dissertations & Theses. 383–389.

Y. C. Hsueh. 2009. et al. Self-tuning Sliding Mode Controller Design for a Class of Nonlinear Control Systems. 2337–2342.

V. Utkin. 2002. Variable Structure Systems with Sliding Modes. Automatic Control, IEEE Transactions on. 22: 212–222.

R. A. DeCarlo, et al. 2002. Variable Structure Control of Nonlinear Multivariable Systems: A Tutorial. Proceedings of the IEEE. 76: 212–232.

K. D. Young, et al. 2002. A Control Engineer's Guide to Sliding Mode Control. 1–14.

O. Kaynak. 2001. Guest Editorial Special Section on Computationally Intelligent Methodologies and Sliding-Mode Control. IEEE Transactions on Industrial Electronics. 48: 2–3.

J. J. Slotine and S. Sastry. 1983. Tracking Control of Non-linear Systems Using Sliding Surfaces, with Application to Robot Manipulators. International Journal of Control. 38: 465–492.

Nekooei, Mohammad Javad, Jaswar, and Agoes Priyanto. 2013. Designing Fuzzy Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control: Applied to Internal Combustion Engine. Applied Mechanics and Materials. 376: 383–389.

Nekooei, Mohammad Javad, Ahmad Afsari, and Hamidreza Khakrah. 2012. Designing Fuzzy Estimator Variable Structure Control: Applied to Internal Combustion Engine. Australian Journal of Basic & Applied Sciences. 6: 13.

Downloads

Published

2014-01-01

Issue

Section

Science and Engineering

How to Cite

Review on Combustion Control of Marine Engine by Fuzzy Logic Control Concerning the Air to Fuel Ratio. (2014). Jurnal Teknologi, 66(2). https://doi.org/10.11113/jt.v66.2493