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The goal of this study was to generate exhaust fast gas data that could be used to identify phenomena that occur before, during, and after stochastic preignition (SPI), also called low-speed preignition (LSPI), events. Crank angle resolved measurement of exhaust hydrocarbons, NO, CO, and CO2 was performed under engine conditions prone to these events. Fuels and engine operating strategies were varied in an attempt to understand similarities and differences in SPI-related behavior that may occur between them. Several different uncommon (typically occurring in less than 1% of engine cycles) features of the fast gas data were identified, and the correlations between them and SPI events were explored. Although the thresholds used to define and identify these observations were arbitrary, they provided a practical means of identifying behavior in the fast gas data and correlating it to SPI occurrence.

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 range 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, with good correlation agreement to PMI. In addition, the paper will cover a global assessment of a gasoline range fuel’s sooting tendency based on the PMI number and the proposed method. Areas around the globe where market gasoline range fuels are of concern will be highlighted, in coordination with the new emissions regulations. Vehicle PM/PN data will also be presented that shows correlations of the indices to the vehicle response.

The Honda Particulate Matter Index (PMI) is a very helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and vehicle OEMs as a metric to understand a fuels impact on automotive engine sooting, in preparation for new global emissions regulations. The calculation of the index involves generating detailed hydrocarbon analysis (hydrocarbon molecular speciation) using gas chromatography laboratory equipment and the PMI calculation requires the exact list of compounds and correct naming conventions to work properly. The analytical methodology can be cumbersome, when the gas chromatography methodology has to be adjusted for new compounds that are not in the method, or if the compounds are not matching the list for quantification. Also, the method itself is relatively expensive, and not easily transferrable between labs.

Two of the goals of the Penn State FutureTruck project were to reduce the emissions of the hybrid electric Ford Explorer to ULEV or lower, and improve the fuel economy by 25% over the stock vehicle. The hybrid electric vehicle system is powered with a 103kW 2.5L Detroit Diesel engine which operates with a fuel blend consisting of ultra-low-sulfur diesel and biodiesel (35%). Lower emissions are inherently achieved by the use of biodiesel. Additionally, the engine was fitted with a series of aftertreatment devices in an effort to achieve the low emissions standards. Vehicle testing has shown a gasoline-equivalent fuel economy improvement of approximately 22%, a reduction in greenhouse gas emissions by approximately 38%, and meeting or exceeding stock emissions numbers in all other categories through the use of an advanced catalyst and control strategy.