Engine knock is among the most relevant limiting factors in the improvement of the operation of spark-ignited engines. Due to an abnormal combustion inside the cylinder chamber, it can cause performance worsening or even serious mechanical damage. Being the result of complex local chemical phenomena, knock turns out to have a significant random behavior but the increasing availability of new on-board sensors permits a deeper understanding of its mechanism. The aim of this paper is to exploit in-cylinder pressure sensors to derive a knock estimator, based on the logistic regression technique. Thanks to the proposed approach, it is possible to explicitly deal with knock random variability and to define the so-called margin (or distance) from the knocking condition, which has been recently proven to be an effective concept for innovative knock control strategies. In a model-based estimation fashion, two modeling approaches are compared: one relies on well-known physical mechanisms while the second exploits a principal component analysis to extract relevant pressure information, thus reducing the identification effort and improving the estimation performance.

Engine Knock Margin Estimation Using In-Cylinder Pressure Measurements

PANZANI, GIULIO;
2017-01-01

Abstract

Engine knock is among the most relevant limiting factors in the improvement of the operation of spark-ignited engines. Due to an abnormal combustion inside the cylinder chamber, it can cause performance worsening or even serious mechanical damage. Being the result of complex local chemical phenomena, knock turns out to have a significant random behavior but the increasing availability of new on-board sensors permits a deeper understanding of its mechanism. The aim of this paper is to exploit in-cylinder pressure sensors to derive a knock estimator, based on the logistic regression technique. Thanks to the proposed approach, it is possible to explicitly deal with knock random variability and to define the so-called margin (or distance) from the knocking condition, which has been recently proven to be an effective concept for innovative knock control strategies. In a model-based estimation fashion, two modeling approaches are compared: one relies on well-known physical mechanisms while the second exploits a principal component analysis to extract relevant pressure information, thus reducing the identification effort and improving the estimation performance.
2017
Engine knock estimation, in-cylinder pressure sensors, knock control, logistic regression, principal component analysis (PCA)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1029604
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