Browse Publications Technical Papers 2023-01-0298

Correlation of Detailed Hydrocarbon Analysis with Simulated Distillation of US Market Gasoline Samples and its Effect on the PEI-SimDis Equation of Calculated Vehicle Particulate Emissions 2023-01-0298

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time. A faster (< 15 min.), but lower resolution chromatography technique known as SimDis, which uses wide bore capillary GC and a flame ionization detector (FID) can be used to analyze a gasoline’s boiling point (volatility) characteristics. The PEISimDis equation was developed using multiple Boiling Point range windows from the SimDis GC analysis relating to the aromatic species identified by the DHA. An enhanced PEISimDis equation is shown [Eq. 5] and has been shown to correlate strongly to other predictive particulate emissions equations such as Particulate Matter Index (PMI) and PEI. The SimDis GC method and subsequent enhanced PEISimDis predictive equation provides a rapid estimate of a gasoline’s tendency to produce vehicle particulate emissions [7].
As a continuation from previous work (P.Geng et al., 2022), this paper presents a study of the correlation of DHA and SimDis, but this time using a wide range of U.S. market gasoline samples.


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