Development of diesel surrogates for reproducing the effect of fuel properties on engine combustion and emissions using an optimized decoupling physical–chemical surrogate (DPCS) model

Abstract An optimized decoupling physical–chemical surrogate (DPCS) model was carried out to formulate different diesel surrogates effectively. In the optimized DPCS model, the physical candidates of ten components and the chemical candidates of four components are coupled by the rule of hydrocarbon type to match the physical–chemical properties of diesel fuel. The composition of the physical components is determined using genetic algorithm (GA), and then the coupling rule is applied to derive the composition of the chemical components. To validate the robustness of the optimized DPCS model, the prediction results are compared with the experimental results containing vapor penetration distance in a constant volume bomb (CVB) and the combustion and emission characteristics in a convention diesel combustion (CDC) engine utilizing different diesel fuels. The results show that the predictions of the diesel surrogates formulated by the optimized DPCS model accurately fit the experimental results, and the impacts of diesel fuel properties on the spray and combustion behaviors can be well reproduced. Besides, the factors that dominate the spray and combustion features of different diesel fuels are identified.