Adaptive Fuzzy Control for Air-Fuel Ratio of Automobile Spark Ignition Engine
In order to meet the limits imposed on automotive
emissions, engine control systems are required to constrain air/fuel
ratio (AFR) in a narrow band around the stoichiometric value, due to
the strong decay of catalyst efficiency in case of rich or lean mixture.
This paper presents a model of a sample spark ignition engine and
demonstrates Simulink-s capabilities to model an internal combustion
engine from the throttle to the crankshaft output. We used welldefined
physical principles supplemented, where appropriate, with
empirical relationships that describe the system-s dynamic behavior
without introducing unnecessary complexity. We also presents a PID
tuning method that uses an adaptive fuzzy system to model the
relationship between the controller gains and the target output
response, with the response specification set by desired percent
overshoot and settling time. The adaptive fuzzy based input-output
model is then used to tune on-line the PID gains for different
response specifications. Experimental results demonstrate that better
performance can be achieved with adaptive fuzzy tuning relative to
similar alternative control strategies. The actual response
specifications with adaptive fuzzy matched the desired response
specifications.
[1] Heywood, J. B. (1988). Internal Combustion Engine Fundumentals. New
York: McGraw-Hill.
[2] Balluchi, A., Benvenuti, L., Di Benedetto, MD., Pinello, C.,
Sangiovanni- Vincentelli, AL., 2000. Automotive engine control and
hybrid systems: challenges and opportunities. Proceedings of the IEEE
88 (7), 888-912.
[3] De Nicolao, G., Scattolini, R., Siviero, C., 1996. Modelling the
volumetric efficiency of IC engines: parametric, non-parametric and
neural techniques. Control Engineering Practice 4 (10), 1405-1415.
[4] Tan, Y., Mehrdad, S., 2000. Neural-networks-based nonlinear dynamic
modeling for automotive engines. Neurocomputing 30, 129-142.
[5] Vinsonneau, J.A.F., Shields, D.N., King, P.J., Burnham, K.J., 2003.
Polynomial and neural network spark ignition engine intake manifold
modeling. Proceedings of the sixteenth International Conference on
Systems Engineering, ICSE-, vol.2, pp. 718-723.
[6] Moskwa J. "Automotive Engine Modeling for Real Time Control" PhD
thesis M.I.T,1998
[7] 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 (D10), 1053-
1068.
[8] Manzie, C., Palaniswami, M., Ralph, D., Watson, H., Yi, X., 2002.
Model predictive control of a fuel injection system with a radial basis
function network observer. Journal of Dynamic Systems Measurement
and Control Transactions of the ASME 124 (4), 648-658.
[9] Choi. S.B., Hendrick, J.K., 1998. An observer-based controller design
method for improving air/fuel characteristics of spark ignition engines.
IEEE Transactions on Control Systems Technology 6 (3), 325-334.
[10] Yoon, R., Sunwoo, M., 2001. An adaptive sliding mode controller for
airfuel ratio control of spark ignition engines. Proceedings of the
Institution of Mechanical Engineers, Part D, Journal of Automobile
Engineering 215, 305-315.
[11] K. Horie, K. Nishizawa, T. Ogawa, S. Akazaki, and K. Miura, "The
Development of a High Fuel Economy and High Performance Four-
Valve Lean Burn Engine", SAE Paper No. 920455, 1992.
[12] T. Inoue, S. Matsushita, K. Nakanishi, and H. Okano, "Toyota Lean
Combustion System - The Third Generation System", SAE Paper No.
930873, 1993
[13] E. H. Mamdani, "Application of fuzzy algorithms for control of simple
dynamic plant," Proc. Inst. Elect. Eng. Contr. Sci., vol. 121, pp. 1585-
1588,1974.
[14] ] L. A. Zadeh, "Outline of a new approach to the analysis of complex
systems and decision processes," IEEE Trans. Syst., Man,
Cybern.,vol.SNC-3,pp. 28-44, 1973.
[15] E. H. Mamdani and S. Assilian, "An experiment in linguistic synthesis
with a fuzzy logic controller," Int. J. Man-Mach. Stud., vol. 7, pp. 1-
13,1975.
[16] ] M. Braae and D. A. Rutherford, "Selection of parameters for a fuzzy
logic controller," Fuzzy Sets Syst., vol. 2, pp. 185-199,1979.
[17] H. Ying, W. Siler, and J. J. Buckley, "Fuzzy control theory: A nonlinear
case," Automatica, vol. 26, pp. 513-520, 1990.
[18] H. Ying, "The simplest fuzzy controllers using different inference
methods are different nonlinear proportional-integral controllers with
variable gains," Automatica, vol. 29, pp. 1579-1589, 1993.
[19] C.-L. Chen and F.-C. Kuo, "Design and analysis of a fuzzy logic
controller," Int. J. Syst. Sci., vol. 29, pp. 1579-1589, 1995.
[20]
[21] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its
applications to modeling and control," IEEE Trans. Syst., Man, Cybern.
vol. SMC-15, pp. 116-132, 1985.
[22] Z.-Y. Zhao, M. Tomizuka, and S. Isaka, "Fuzzy gain scheduling of PID
controllers," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 1392-
1398,1993.
[23] C. W. de Silva, Intelligent Control: Fuzzy Logic Applications.
NewYork: CRC, 1995.
[24] B.-G. Hu, G. K. I. Mann, and R. G. Gosine, "Theoritic and genetic
design of a three-rule fuzzy PI controller," in Proc. 6th IEEE Int. Conf.
Fuzzy Systems, Barcelona, Spain, July 1-5, 1997, vol. 1, pp. 489-496.
[25] Haluska, P., & Guzzella, L. (1998). Control oriented modeling of
mixture formation phenomena in multi-port injection SI gasoline
engines. In T. Morel (Ed.), SAE Special Publication (Vol. SP-1330),
SAE Paper 980628. Warrendale: Sae International.
[26] Aquino, C. F. (1981). Transient A/F control characteristics of the 5 liter
central fuel injection engine. SAE Paper 810494, Sae International,
Warrendale.
[27] Hendricks E., Sorenson S.C. "SI engine control and mean value engine
modeling"SAE 910258,1991.
[28] Gambino, M., Pianese, C., & Rizzo, G. (1994). Identification of a
dynamic model for transient mixture formation in a multipoint spark
ignition engine. Proceedings of Fourth ASME Symposium on
Transportation Systems (DSC-Vol. 54, pp. 189-204), Chicago.
[29] Arsie , C.Pianese , G. Rizzo , V. Cioffi ., 2002. An adaptive estimator of
fuel film dynamics in the intake port of a spark ignition engine.IEEE
[30] Hendricks E. "A generic mean value engine model for spark ignition
engines."SIMS 2000.
[31] Hendricks E.,Chevalier A., Jensen A., Sorenson S.C. "Modelling of the
intake manifold filling dynamics."SAE paper 960037,1996.
[32] D. L. Stivender, "Engine air control - basis of a vehicular systems
control hierarchy," SAE Paper No. 780346, 1978.
[33] R. L. Woods, "An air-modulated fluidic fuel-injection system," ASME J.
Dyn. Sys., Meas., and Contr., vol. 101, pp. 71-76, Mar. 1979
[34] N. Gulley, and J.S.R. Jang, Fuzzy logic toolbox: user-s guide, The
MATHWORKS, Inc., 2000.
[35] S.W. Wang, D.L. Yu , J.B. Gomm, G.F. Page, S.S. Douglas., "Adaptive
neural network model based predictive control for air-fuel ratio of SI
engine", . Engineering Applications of Artificial Intelligence 19 (2006)
189-200.
[1] Heywood, J. B. (1988). Internal Combustion Engine Fundumentals. New
York: McGraw-Hill.
[2] Balluchi, A., Benvenuti, L., Di Benedetto, MD., Pinello, C.,
Sangiovanni- Vincentelli, AL., 2000. Automotive engine control and
hybrid systems: challenges and opportunities. Proceedings of the IEEE
88 (7), 888-912.
[3] De Nicolao, G., Scattolini, R., Siviero, C., 1996. Modelling the
volumetric efficiency of IC engines: parametric, non-parametric and
neural techniques. Control Engineering Practice 4 (10), 1405-1415.
[4] Tan, Y., Mehrdad, S., 2000. Neural-networks-based nonlinear dynamic
modeling for automotive engines. Neurocomputing 30, 129-142.
[5] Vinsonneau, J.A.F., Shields, D.N., King, P.J., Burnham, K.J., 2003.
Polynomial and neural network spark ignition engine intake manifold
modeling. Proceedings of the sixteenth International Conference on
Systems Engineering, ICSE-, vol.2, pp. 718-723.
[6] Moskwa J. "Automotive Engine Modeling for Real Time Control" PhD
thesis M.I.T,1998
[7] 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 (D10), 1053-
1068.
[8] Manzie, C., Palaniswami, M., Ralph, D., Watson, H., Yi, X., 2002.
Model predictive control of a fuel injection system with a radial basis
function network observer. Journal of Dynamic Systems Measurement
and Control Transactions of the ASME 124 (4), 648-658.
[9] Choi. S.B., Hendrick, J.K., 1998. An observer-based controller design
method for improving air/fuel characteristics of spark ignition engines.
IEEE Transactions on Control Systems Technology 6 (3), 325-334.
[10] Yoon, R., Sunwoo, M., 2001. An adaptive sliding mode controller for
airfuel ratio control of spark ignition engines. Proceedings of the
Institution of Mechanical Engineers, Part D, Journal of Automobile
Engineering 215, 305-315.
[11] K. Horie, K. Nishizawa, T. Ogawa, S. Akazaki, and K. Miura, "The
Development of a High Fuel Economy and High Performance Four-
Valve Lean Burn Engine", SAE Paper No. 920455, 1992.
[12] T. Inoue, S. Matsushita, K. Nakanishi, and H. Okano, "Toyota Lean
Combustion System - The Third Generation System", SAE Paper No.
930873, 1993
[13] E. H. Mamdani, "Application of fuzzy algorithms for control of simple
dynamic plant," Proc. Inst. Elect. Eng. Contr. Sci., vol. 121, pp. 1585-
1588,1974.
[14] ] L. A. Zadeh, "Outline of a new approach to the analysis of complex
systems and decision processes," IEEE Trans. Syst., Man,
Cybern.,vol.SNC-3,pp. 28-44, 1973.
[15] E. H. Mamdani and S. Assilian, "An experiment in linguistic synthesis
with a fuzzy logic controller," Int. J. Man-Mach. Stud., vol. 7, pp. 1-
13,1975.
[16] ] M. Braae and D. A. Rutherford, "Selection of parameters for a fuzzy
logic controller," Fuzzy Sets Syst., vol. 2, pp. 185-199,1979.
[17] H. Ying, W. Siler, and J. J. Buckley, "Fuzzy control theory: A nonlinear
case," Automatica, vol. 26, pp. 513-520, 1990.
[18] H. Ying, "The simplest fuzzy controllers using different inference
methods are different nonlinear proportional-integral controllers with
variable gains," Automatica, vol. 29, pp. 1579-1589, 1993.
[19] C.-L. Chen and F.-C. Kuo, "Design and analysis of a fuzzy logic
controller," Int. J. Syst. Sci., vol. 29, pp. 1579-1589, 1995.
[20]
[21] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its
applications to modeling and control," IEEE Trans. Syst., Man, Cybern.
vol. SMC-15, pp. 116-132, 1985.
[22] Z.-Y. Zhao, M. Tomizuka, and S. Isaka, "Fuzzy gain scheduling of PID
controllers," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 1392-
1398,1993.
[23] C. W. de Silva, Intelligent Control: Fuzzy Logic Applications.
NewYork: CRC, 1995.
[24] B.-G. Hu, G. K. I. Mann, and R. G. Gosine, "Theoritic and genetic
design of a three-rule fuzzy PI controller," in Proc. 6th IEEE Int. Conf.
Fuzzy Systems, Barcelona, Spain, July 1-5, 1997, vol. 1, pp. 489-496.
[25] Haluska, P., & Guzzella, L. (1998). Control oriented modeling of
mixture formation phenomena in multi-port injection SI gasoline
engines. In T. Morel (Ed.), SAE Special Publication (Vol. SP-1330),
SAE Paper 980628. Warrendale: Sae International.
[26] Aquino, C. F. (1981). Transient A/F control characteristics of the 5 liter
central fuel injection engine. SAE Paper 810494, Sae International,
Warrendale.
[27] Hendricks E., Sorenson S.C. "SI engine control and mean value engine
modeling"SAE 910258,1991.
[28] Gambino, M., Pianese, C., & Rizzo, G. (1994). Identification of a
dynamic model for transient mixture formation in a multipoint spark
ignition engine. Proceedings of Fourth ASME Symposium on
Transportation Systems (DSC-Vol. 54, pp. 189-204), Chicago.
[29] Arsie , C.Pianese , G. Rizzo , V. Cioffi ., 2002. An adaptive estimator of
fuel film dynamics in the intake port of a spark ignition engine.IEEE
[30] Hendricks E. "A generic mean value engine model for spark ignition
engines."SIMS 2000.
[31] Hendricks E.,Chevalier A., Jensen A., Sorenson S.C. "Modelling of the
intake manifold filling dynamics."SAE paper 960037,1996.
[32] D. L. Stivender, "Engine air control - basis of a vehicular systems
control hierarchy," SAE Paper No. 780346, 1978.
[33] R. L. Woods, "An air-modulated fluidic fuel-injection system," ASME J.
Dyn. Sys., Meas., and Contr., vol. 101, pp. 71-76, Mar. 1979
[34] N. Gulley, and J.S.R. Jang, Fuzzy logic toolbox: user-s guide, The
MATHWORKS, Inc., 2000.
[35] S.W. Wang, D.L. Yu , J.B. Gomm, G.F. Page, S.S. Douglas., "Adaptive
neural network model based predictive control for air-fuel ratio of SI
engine", . Engineering Applications of Artificial Intelligence 19 (2006)
189-200.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:59504", author = "Ali Ghaffari and A. Hosein Shamekhi and Akbar Saki and Ehsan Kamrani", title = "Adaptive Fuzzy Control for Air-Fuel Ratio of Automobile Spark Ignition Engine", abstract = "In order to meet the limits imposed on automotive
emissions, engine control systems are required to constrain air/fuel
ratio (AFR) in a narrow band around the stoichiometric value, due to
the strong decay of catalyst efficiency in case of rich or lean mixture.
This paper presents a model of a sample spark ignition engine and
demonstrates Simulink-s capabilities to model an internal combustion
engine from the throttle to the crankshaft output. We used welldefined
physical principles supplemented, where appropriate, with
empirical relationships that describe the system-s dynamic behavior
without introducing unnecessary complexity. We also presents a PID
tuning method that uses an adaptive fuzzy system to model the
relationship between the controller gains and the target output
response, with the response specification set by desired percent
overshoot and settling time. The adaptive fuzzy based input-output
model is then used to tune on-line the PID gains for different
response specifications. Experimental results demonstrate that better
performance can be achieved with adaptive fuzzy tuning relative to
similar alternative control strategies. The actual response
specifications with adaptive fuzzy matched the desired response
specifications.", keywords = "Modelling, Air–fuel ratio control, SI engine,Adaptive fuzzy Control.", volume = "2", number = "12", pages = "1331-9", }
