On the performance of biodiesel blends-experimental data and simulations using a stochastic fuel test bench

Andrea Matrisciano, Michal Pasternak, Xiaoxiao Wang, Oleksiy Antoshkiv, Fabian Mauss, Peter Berg

Abstract

In this work are presented experimental and simulated data from a one-cylinder direct injected Diesel engine fuelled with Diesel, two different biodiesel blends and pure biodiesel at one engine operating point. The modeling approach focuses on testing and rating biodiesel surrogate fuel blends by means of combustion and emission behavior. Detailed kinetic mechanisms are adopted to evaluate the fuel-blends performances under both reactor and diesel engine conditions. In the first part of the paper, the experimental engine setup is presented. Thereafter the choice of the surrogate fuel blends, consisting of n-decane, α-methyl-naphtalene and methyl-decanoate, are verified by the help of experiments from the literature. The direct injection stochastic reactor model (DI-SRM) is employed to simulate combustion and engine exhaust emissions (NO_x, HC, CO and CO₂), which are compared to the experimental data. For this the mixing time is used as main modeled parameter, which is deduced from regular Diesel experiments. The investigation shows that the considered modeling approach can be used to simulate Diesel engine performance and compare the quality of biodiesel blends.