A CFD Study on Mixture Preparation and Combustion in a Heavy-Duty Locomotive Diesel Engine at High Load Condition

Abstract Diesel engines are one of the most commonly used combustion systems for heavy-duty applications like locomotives. Although computational fluid dynamics (CFD) modeling of diesel engines is a mature research topic, CFD modeling of large-bore engines like those used in locomotives has not been as extensively studied as their smaller bore on-road and stationary counterparts. The present paper aims at identifying and outlining best practices for performing 3D CFD simulations of locomotive diesel engines and comparing them with the established best practices for heavy-duty diesel engines in the literature. The locomotive diesel engine considered in this study has a bore of 168mm and operates at speeds of up to 1800 rpm. Open cycle engine CFD simulations were carried out for both motored and fired cases. Two turbulence models viz., Re-Normalization group (RNG) k-ε model and Reynolds stress model (RSM) were used in this study to assess their performance. The fuel spray break up was modelled using Kelvin Helmholtz and Rayleigh Taylor (KH-RT) model. A grid and statistical convergence study was performed to assess the effect of mesh size on the predicted results. It was found that a minimum cell size of 0.25 mm near the fuel spray and 1 mm in the rest of the cylinder was sufficient to achieve grid convergence in terms of spray and combustion characteristics. The boundary wall temperatures are shown to affect the in-cylinder pressure predictions. Higher wall temperatures were found to reduce the trapped mass and increase the peak motored pressure. The CFD model was validated by comparing the simulation results with the experimental measurements at full rated power. It was found that the RSM was able to capture the combustion characteristics more accurately compared to RNG k-ε model. Overall, the CFD model was able to predict the engine combustion and performance characteristics at three injection timings.