» Download Article

Authors
Arsie, I.; Sorrentino, M.; Pianese, C.

Identifier
10.3182/20070820-3-US-2918.00032

Index Terms
nonlinear dynamic modeling,neural networks,engine modeling,engine control,diagnostics

Abstract
The paper focuses on the experimental identification and validation of a recurrent neural network (RNN) estimator of air-fuel ratio (AFR) excursions in sparkignited engines. Suited training procedures and experimental tests are proposed to improve RNN precision and generalization in predicting AFR transients for a wide range of operating scenarios. The reference engine has been tested by means of an integrated system of hardware and software tools for engine test automation and control strategies prototyping. The simulation performed on the test-sets show the ability of the RNN to reproduce the target patterns with satisfactory accuracy. The results achieved envisage potential applications of the AFR estimator in real-time diagnostics and control algorithms.

References

[1] Aquino, C.F., 1981, "Transient A/F Control
    Characteristics of the 5 Liter Central Fuel
    Injection Engine", SAE paper 810494.
[2] Arsie, I., Marotta, M.M., Pianese, C., and Sorrentino,
    M., 2006a, "Experimental Validation of a Neural
    Network Based A/F Virtual Sensor for SI Engine
    Control", SAE paper 2006-01-1351.
[3] Arsie, I., Pianese, C., and Sorrentino, M., 2004,
    "Nonlinear Recurrent Neural Networks for Air
    Fuel Ratio Control in SI engines", SAE paper
    2004-01-1364.
[4] Arsie, I., Pianese, C., and Sorrentino, M., 2006b, "A
    procedure to enhance identification of recurrent
    neural networks for simulating air-fuel ratio
    dynamics in SI engines", Engineering
    Applications of Artificial Intelligence 19 (1), pp.
    65-77.
[5] Arsie, I., Pianese, C., Rizzo, G., and Cioffi, V.,
    2003a, "An Adaptive Estimator of Fuel Film
    Dynamics in the Intake Port of a Spark Ignition
    Engine", Control Engineering Practice, vol. 11,
    no. 3, pp. 303-309.
[6] Capriglione, D., Liguori, C., Pianese, C., and
    Pietrosanto, A., 2003, "On-line Sensor Fault
    Detection Isolation, and Accomodation in
    Automotive Engines", IEEE Transactions on
    Instrumentation and Measurement, Vol. 52, No.
    4, pp. 1182-1189.
[7] Choi, S.B., and Hedrick, J.K., "An Observer-Based
    Controller Design Method for Improving
    Air/Fuel Characteristics of Spark Ignition
    Engines", IEEE Transactions on Control Systems
    Technology, Vol. 6, No. 3, May 1998.
[8] Dovifaaz, X., Ouladsine, M., and Rachid, A., 1999,
    "Optimal Control of a Turbocharged Diesel
    Engine Using Neural Network", Proceedings of
    the 14th IFAC World Congress, IFAC-8b-009,
    Beijing, China, July 5-9, 1999.
[9] Haykin, S., 1999, Neural Networks, Prentice Hall.
[10] Hendricks, E., and Sorenson, S.C., 1991, "SI Engine
     Controls and Mean Value Engine Modeling",
     SAE Paper 910258.
[11] Kolmogorov A..N. (1965), On the Representation of
     Continuous Functions of Many Variables by
     Superposition of Continuous Functions of One
     Variable and Addition, Amer. Math. Society
     Translations, 28, pp. 55-59, 1965.
[12] Maloney, P. J., "A Production Wide-Range AFR -
     Response Diagnostic Algorithm for Direct-Injection
      Gasoline Application", SAE Paper
     2001-01-0558, 2001.
[13] Nørgaard, M., Ravn, O., Poulsen, N.L., and Hansen,
     L.K., 2000, Neural Networks for Modelling and
     Control of Dynamic Systems, Springer-Verlag.
[14] Onder, C. H., Roduner, C. A., and Geering, H. P.,
     "Model Identification for the A/F Path of an SI
     Engine", SAE Paper 970612, 1997.
[15] Ortmann, S., Glesner, M., Rychetsky, M., Tubetti, P.,
     and Morra, G., 1998, "Engine Knock Estimation
     Using Neural Networks based on a Real-World
     Database", SAE Paper 980513.
[16] Patterson, D.W., 1995, Artificial Neural Networks -
     Theory and Applications, Prentice Hall.
[17] Powell, J.D., Fekete, N.P., and Chang, C.F., 1998,
     "Observer-Based Air-Fuel Ratio Control", IEEE
     Transactions on Control Systems, vol. 18, no. 5,
     pp. 72-83.
[18] Shayler, P.J., Goodman, M.S., and Ma, T., 1996,
     "Transient Air/Fuel Ratio Control of an S.I.
     Engine Using Neural Networks", SAE Paper
     960326.
[19] Tan, Y., and Saif, M., 2000, "Neural-networks-based
     nonlinear dynamic modeling for automotive
     engines", Neurocomputing, vol. 30, pp. 129-142.
[20] Turin, R.C., and Geering, H.P., 1994, "Model-Based
     Adaptive Fuel Control in an SI Engine", SAE
     Paper 940374.
[21] Vigild, C.W., Andersen, K.P.H., and Hendricks, E.,
     1999, "Towards Robust H-infinity Control of an
     SI Engine's Air/Fuel Ratio", SAE Paper 1999-
     01-0854.
[22] Yasuri, Y., Shusuke, A., Ueno, M., and Yoshihisa, I.,
     2000, "Secondary O2 Feedback Using Prediction
     and Identification Type Sliding Mode Control",
     SAE Paper no. 2000-01-0936.
[23] Yoo, I.K., Upadhyay, D., and Rizzoni, G., 1999, "A
     Control-Oriented Carbon Canister Model", SAE
     Paper 1999-01-1103.