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Controlling Low-Speed Pre-Ignition in Modern Automotive Equipment Part 3: Identification of Key Additive Component Types and Other Lubricant Composition Effects on Low-Speed Pre-Ignition

Journal Article
2016-01-0717
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 05, 2016 by SAE International in United States
Controlling Low-Speed Pre-Ignition in Modern Automotive Equipment Part 3: Identification of Key Additive Component Types and Other Lubricant Composition Effects on Low-Speed Pre-Ignition
Sector:
Citation: Ritchie, A., Boese, D., and Young, A., "Controlling Low-Speed Pre-Ignition in Modern Automotive Equipment Part 3: Identification of Key Additive Component Types and Other Lubricant Composition Effects on Low-Speed Pre-Ignition," SAE Int. J. Engines 9(2):832-840, 2016, https://doi.org/10.4271/2016-01-0717.
Language: English

Abstract:

Market demand and evolving global legislation are forcing OEMs to improve fuel consumption and reduce CO2 emissions. Downsizing in direct injection gasoline engines has been a common strategy towards achieving this goal, but this requires increased boost pressures to maintain power. The increased boost pressures are creating a new abnormal combustion phenomenon known as Low-Speed Pre-Ignition (LSPI).
Lubricants and fuels have been implicated as significant influencers of LSPI frequency and intensity. Part 1 of the series described the development of a statistical approach for measuring and quantifying LSPI activity. This statistical approach was shown to be consistent and repeatable. Part 2 of the series further refined the methodology from Part 1 to reduce the frequency of false positives and negatives. A baseline lubricant was used in both of these papers to demonstrate the robustness of this methodology.
This paper explores major lubricant components in order to assess their impact on LSPI activity as promoters, quenchers or having no effect (neutral) on LSPI based on this baseline lubricant, with a strong focus on the most common metal detergent cations used in modern automotive lubricants. It also raises concerns about using general LSPI prediction equations, particularly concerning their accuracy with poor quality fuels.