The effect of fuel composition on particulate emissions from a highly boosted GDI engine - an evaluation of three particulate indices

Sam Akehurst, James Turner, Andrew Lewis, Felix Leach, Richard Stone, Roger Cracknell, Varun Shankar, David Richardson

Research output: Contribution to journalArticlepeer-review

40 Citations (SciVal)

Abstract

Gasoline Direct Injection (GDI) engines equipped with a turbocharger or supercharger (known as boosted engines) have achieved significant market penetration due to their advantages in reducing CO2 emissions compared to Port Fuel Injection (PFI) engines. These engines are known to emit particulate matter and recent studies have characterized these emissions. Fuel composition is known to have an impact on Particle Number (PN) emissions from GDI engines, however its effect on emissions from highly boosted engines is not known.

In this work, 10 different fuels have been tested on an extremely highly boosted engine (at up to 35 bar BMEP) at several different operating conditions both unboosted and boosted and the PN emissions and size distributions have been measured using a Cambustion DMS500. The applicability of three previously developed indices linking fuel composition to PN emissions is tested with the results from these fuels.

The results show that the PM index is a good predictor of PN emissions from this engine for all fuels at all operating points (unboosted and boosted). The Moriya and PN indices predict the PN emissions using fuels that are market representative, but are poor predictors of PN emissions over all of the fuels tested. Very small accumulation mode particle sizes of around 30 nm have been noted from all fuels at boosted conditions, which has relevance to future legislation and after treatment.
Original languageEnglish
Pages (from-to)598-611
Number of pages14
JournalFuel
Volume252
Early online date6 May 2019
DOIs
Publication statusPublished - 15 Sept 2019

Fingerprint

Dive into the research topics of 'The effect of fuel composition on particulate emissions from a highly boosted GDI engine - an evaluation of three particulate indices'. Together they form a unique fingerprint.

Cite this