Knock Analysis in the Crank Angle Domain for Low-Knocking Cycles Detection

Knock is an abnormal phenomenon with in-cylinder pressure oscillations, which must be avoided to protect the engine from damage and to avoid excessive noise. Conventional control algorithms delay the combustion with the spark to avoid high knocking rates but reduce the thermal efficiency and restricts the performance of a spark ignition engine. The detection and characterization of low-knocking cycles might be used for improving knock control algorithms, however, it is a challenging task, as normal combustion also excite the different resonance modes and might be confused with knock. Most of the methods found in literature for knock detection use 0-Dimensional indicators, regardless of the angular evolution of the pressure oscillations. In this paper, the in-cylinder pressure oscillations evolution during the piston stroke is analyzed by using various time-frequency transformations. The analysis highlights the need of a new criteria for knock detection, which must take into account the intensity of the oscillations but also the crank angle location where they take place. A new definition of knock is proposed by using resonance to design an indicator of the pressure resonance evolution and by assuming constant volume combustion at knock to determine the minimum oscillation required for end-gas auto ignition detection as a function of the crank angle location. Several experimental tests with an EURO VI SI engine are used for illustration and validation purposes. A conventional knock control algorithm was used for comparing the new knock event definition with the classical MAPO definition, being the new indicator able to improve the performance of the controllers by giving more information about knock and introducing lower spark advance (SA) variability.


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  • Accession Number: 01739909
  • Record Type: Publication
  • Source Agency: SAE International
  • Report/Paper Numbers: 2020-01-0549
  • Files: TRIS, SAE
  • Created Date: May 26 2020 10:16AM