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Engine Management without Air Mass Flow Meter
Published June 12, 2000 by Society of Automotive Engineers of Korea in South Korea
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The need for a stoichiometric air-to-fuel ratio in an SI engine with a catalytic converter makes the accurate knowledge of the air and fuel paths indispensable. This investigation is focused on the prediction of the air mass flow into the cylinder without the use of an air mass flow meter. A dynamical mean value engine model of the intake manifold has been derived. Combining a gain-scheduling and a self-tuning algorithm has been found to be a good strategy for the persistent adaptation of the intake manifold model to the changing ambient conditions and actuator parameters such as aging or malfunctions.
The adaptation algorithm is based on the direct identification of the air mass flows entering and leaving the intake manifold, thus the identified parameters can be interpreted as the throttle and the filling characteristics.
The recursive least squares algorithm has been used for parameter identification. Different modelling approaches and discretization methods have been applied for parametrization. The direct identification of the air mass flows by use of bilinear discretization techniques has brought the best results.
To reduce the noise level, a segment filter for identification has been developed. It calculates the mean value of the measure d signal from a collection of oversampled data. The use of the least squares algorithm has been shown to be a good approach to the prediction of the air mass in the cylinder without using an air mass flow meter. Yet the sensitivity of the least squares algorithm against coloured noise necessitates the investigation of other algorithms.
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- Theophil S. Auckenthaler - Measurement and Control Laboratory, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland
- Christopher H. Onder - Measurement and Control Laboratory, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland
- Hans P. Geering - Measurement and Control Laboratory, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland
CitationAuckenthaler, T., Onder, C., and Geering, H., "Engine Management without Air Mass Flow Meter," SAE Technical Paper 2000-05-0091, 2000.
- Turin, R. Untersuchung modellbasierter, adaptiver Verfahren zur Kompensation der Gemischbildungsdynamik eines Otto-Motors, Dissertation Nr. 9999 ETH Zürich 1992
- Onder, C. Modellbasierte Optimierung der Steuerung und Regelung eines Automobilmotors, Dissertation Nr. 10323 ETH Zürich 1993
- Bidan, P. Boverie, S. Chaumerliac, V Nonlinear Control of a Spark-Ignition Engine IEEE Transactions on Automatic Control 3 1 March 1995
- Hendricks, E. et al. Modelling of the Intake Manifold Filling Dynamics SAE Paper No. 960037 1996
- Aquino, C.F. Transient A/F Control Characteristics of the 5 Liter Central Fuel Injection Engine SAE Paper No. 810494 1981
- Åström, K. Wittenmark, B. Adaptive control 2nd edition Addison-Wesley 1995
- Ljung, L. System Identification, theory for the user Prentice-Hall New Jersey 1987
- Franklin, Powell Workman: Digital Control of Dynamic Systems Addison-Wesley 1990