Predicting the combustion behavior of straight soybean oil/diesel blends: an integrated numerical and experimental assessment

Abstract

Abstract This study presents a numerical characterization of the combustion process of straight soybean oil (SSO)/diesel blends using the AVL BOOST™ engine model. Validated against experimental data from a single-cylinder Yanmar YT22E engine, the work investigates four blend compositions (100% diesel, 50% diesel + 50% straight soybean oil, and 20% diesel + 80% straight soybean oil) at pre-heating temperatures of $$25^\circ$$ C and $$85^\circ$$ C and three engine speeds (1800, 2100 and 2200 rpm). Numerical simulations successfully predicted performance trends, revealing a decrease in injected fuel mass per cycle (IMFC) of up to 13% at 2200 rpm for pre-heated blends. Although the model estimated lower brake power and torque, with discrepancies ranging from 2.7% to 9.0% attributed to comprehensive manifold heat loss modeling, the combustion phasing (CA10 and CA50) and heat release rate (HRR) showed high correlation with experimental benchmarks. The results confirm that methyl linoleate is an effective surrogate for soybean oil in zero-dimensional modeling, providing a robust framework for predicting the behavior of high-viscosity biofuels.