Critical Analysis of PM Index and Other Fuel Indices: Impact of Gasoline Fuel Volatility and Chemical Composition IFP Energies Nouvelles, Institut Carnot IFPEN TE

Format:

Conference/Event

Author/Creator:

Ben Amara, Ben Amara, author.

Contributor:

IIda, Yutaka

KOJI, Nagata

Moriya, Hidenori

Starck, Laurie

Tahtouh, Toni

Ubrich, Elisabeth

Conference Name:

International Powertrains, Fuels & Lubricants Meeting (2018-09-17 : Heidelberg, Germany)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2018

Summary:

AbstractAmong the challenges for the future facing the development of gasoline engines, one of the most important is the reduction of particles emissions. This study proposes a critical and objective evaluation of the influence of fuel characteristics on gasoline particles emission through the use of Fuel Particle Indices. For this, a selected fuel matrix composed of 22 fuels was built presenting different volatility and chemical composition (content in total aromatics, heavy cuts and ethanol). To represent the fuel sooting tendency, seven Fuel Particle Indices were selected based on a literature review, namely, Particulate Matter Index (PMI), Particulate Number index (PNI), Threshold Sooting index (TSI), Smoke point (SP), Oxygen Extended Sooting Index (OESI), Simplified index 1 and 2 (sPMI 1, sPMI 2). These indices were computed on the fuel matrix and compared on the basis of three main axes. First, the sensitivity to fuel variation. Second, the agreement with engine particles emissions measured on vehicle on three vehicles. Third, the ease to compute with respect to the data availability in the European standard EN228. The comparison of fuel particles indices revealed different sensitivities to fuel variation: PMI, sPMI 1 and sPMI 2 represent well the effects of heavy aromatics, PNI is highly sensitive to the DVPE whereas SP, OESI and TSI were found well representative of the total aromatic content but represent weakly the effect of heavy aromatics. The comparison of the fuel particles indices with engine data indicates a good agreement of all indices, except for PNI. Finally, sPMI 1, sPMI 2 and calculated SP were found to be much easier to compute because they need simple data as input. This work highlights the importance of fuel quality on the reduction of particles emissions and suggests relevant Fuel Particles Indices that allow to capture fuel variation

Notes:

Vendor supplied data

Publisher Number:

2018-01-1741

Access Restriction:

Restricted for use by site license