Enhanced model and fuzzy strategy of air to fuel ratio control for spark ignition engines

Various mathematical models for the air to fuel ratio and control for spark ignition (SI) engines have been proposed to satisfy technical specifications. This paper reveals an improvement of the mean value model (MVEM) and a simple yet effective nonlinear control to enhance the air to fuel regulator. The regulator is designed by using a discrete fuzzy PI algorithm, which provides easy tuning, robustness, and rapid development with a simple architecture. Effects on the dead time, exhausted delay, time-varying air flow and chaotic disturbance are also included. The computer simulation results show satisfactory performance based on standard evaluation criteria. The proposed model has a great potential for practical implementations.

[1]  Uwe Kiencke,et al.  Automotive Control Systems: For Engine, Driveline, and Vehicle , 2000 .

[2]  J. Karl Hedrick,et al.  An observer-based controller design method for improving air/fuel characteristics of spark ignition engines , 1998, IEEE Trans. Control. Syst. Technol..

[3]  Aamer I. Bhatti,et al.  Estimating SI Engine Efficiencies and Parameters in Second-Order Sliding Modes , 2011, IEEE Transactions on Industrial Electronics.

[4]  J. David Powell,et al.  Air-fuel ratio control in spark-ignition engines using estimation theory , 1995, IEEE Trans. Control. Syst. Technol..

[5]  Guanrong Chen,et al.  Stability analysis of nonlinear fuzzy PI control systems , 1993, Third International Conference on Industrial Fuzzy Control and Intelligent Systems.

[6]  Shiwei Wang,et al.  A New Development of Internal Combustion Engine Air-Fuel Ratio Control With Second-Order Sliding Mode , 2007 .

[7]  C. R. Ferguson Internal Combustion Engines: Applied Thermosciences , 1986 .

[8]  Umberto Montanaro,et al.  Model-Based Control of the Air Fuel Ratio for Gasoline Direct Injection Engines via Advanced Co-Simulation: An Approach to Reduce the Development Cycle of Engine Control Systems , 2011 .

[9]  S. S. Douglas,et al.  Adaptive neural network model based predictive control for air-fuel ratio of SI engines , 2006, Eng. Appl. Artif. Intell..

[10]  Richard Burton,et al.  Neural network control of air-to-fuel ratio in a bi-fuel engine , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[11]  Dingli Yu,et al.  Adaptive RBF network for parameter estimation and stable air-fuel ratio control , 2008, Neural Networks.

[12]  Karolos M. Grigoriadis,et al.  Linear parameter-varying lean burn air-fuel ratio control for a spark ignition engine , 2007 .

[13]  Matthew A. Franchek,et al.  Transient Fueling Controller Identification for Spark Ignition Engines , 2006 .

[14]  George E. Totten,et al.  Handbook of Lubrication and Tribology : Volume I Application and Maintenance, Second Edition , 2006 .

[15]  Gene F. Franklin,et al.  Feedback Control of Dynamic Systems , 1986 .

[16]  John J. Moskwa,et al.  Automotive Engine Modeling for Real-Time Control Using MATLAB/SIMULINK , 1995 .

[17]  YangQuan Chen,et al.  Linear Feedback Control: Analysis and Design with MATLAB , 2008 .