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The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation.

A gasoline’s chemical composition impacts a vehicle’s sooting tendency and therefore has been the subject of numerous emissions studies. From these studies, several mathematical correlation equations have been developed to predict a gasoline’s sooting tendency in modern spark-ignited internal combustion engine vehicles. This paper reviews the recently developed predictive tool methods and summarizes five years of global market fuel survey data to characterize gasoline sooting tendency trends around the world. Additionally, the paper will evaluate and suggest changes to the predictive methods to improve emissions correlations.

In order to further understand the sequence of events leading to stochastic preignition in a spark-ignition engine, a methodology previously developed by the authors was used to evaluate the propensity of a wide range of fuels to establishing propagating flames under conditions representative of those at which stochastic preignition (SPI) occurs. The fuel matrix included single component hydrocarbons, binary mixtures, and real fuel blends. The propensity of each fuel to establish a flame was correlated to multiple fuel properties and shown to exhibit consistent blending behaviors. No single parameter strongly predicted a fuel’s propensity to establish a flame, while multiple reactivity-based parameters exhibited moderate correlation. A two-stage model of the flame establishment process was developed to interpret and explain these results.

The Particulate Matter Index (PMI) is a helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and OEMs as a metric to understand the gasoline fuels impact on both sooting found on engine hardware and vehicle out emissions. This paper will explore a new method that could be used to give indication of the sooting tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), and provide the detailed equation in its initial form. In addition, the PEI will be shown to have a good correlation agreement to PMI. The paper will then give a detailed explanation of the data used to develop it. Initial vehicle PM/PN data will also be presented that shows correlations of the indices to the vehicle response.

Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work.

The impact of gasoline composition on vehicle particulate emissions response has been widely investigated and documented. Correlation equations between fuel composition and particulate emissions have also been documented, e.g. Particulate Matter Index (PMI) and Particulate Evaluation Index (PEI). Vehicle PM/PN emissions correlate very well with these indices. In a previous paper, global assessment with PEI on fuel sooting tendency was presented [1]. This paper will continue the previous theme by the authors, and cover China gasoline in more detail. With air pollution an increasing concern, along with more stringent emission requirements in China, both OEMs and oil industries are facing new challenges. Emissions controls require a systematic approach on both fuels and vehicles. Chinese production vehicle particulate emissions for a range of PEI fuels are also presented.