Surrogate Generation and Evaluation for Diesel Fuel

Abstract

The correct representation of a fuel in terms of its physical and chemical properties and its combustion kinetics poses a challenge to modern engine development when state-of-the-art simulation technology is used. In this context, a promising approach is the use of surrogates that emulate the properties of real fuels, where the surrogates are made up of a significantly lower number of components than the original fuels. The goal of this paper is to present an algorithm that can be used to generate surrogates composed of real chemical components, as opposed to pseudo-components. The algorithm was developed by simultaneously fitting the true boiling point (TBP) curve, the liquid density at 15 °C, and the cetane number. To illustrate the algorithm, surrogates for four different fuels were generated: a commercially available European diesel and three research diesel proposed by the Fuels for Advanced Combustion Engines (FACE) CRC Research Group. Two of the resulting surrogates were produced on a lab scale and subjected to laboratory examination. For validation, the experimental data for these two surrogates were compared to those for the target fuels and to data generated by thermodynamic models on the basis of the compositions of the surrogates. Both the fitted properties and additional properties, which were not used for fitting, were compared to experimental properties, such as the ASTM D86 boiling curve, content of aromatics, flash point, heating value, cloud point, viscosity, and temperature dependency of the liquid-phase viscosity and density. We demonstrate that the proposed algorithm generates surrogates of approximately 10 real components, which show excellent agreement with the original target fuels.