2.1.Model Construction

The engine used in this study is a four-cylinder, four-stroke diesel engine. The main parameters of the engine are provided in Table 1, and the combustion chamber is a deep-pit ω-type. A schematic of the engine test bench is shown in Figure 1. The test was conducted at an altitude of 2000 m, with an atmospheric pressure of 81 kPa in the testing environment. The simulation model parameters were set according to the experimental control parameters. A geometric model of the engine combustion chamber was created using UG NX 2023 software (Version 2023, Siemens Digital Industries Software, Plano, TX, USA) and imported into CONVERGE 3.0 for preprocessing and mesh generation. Subsequently, CFD simulations of the combustion process were conducted. CONVERGE 3.0 utilizes automatically generated dynamic moving meshes, with local mesh refinement applied to the cylinder head, piston crown, and injector nozzle regions to more accurately capture the complex velocity gradients and fuel mixing characteristics in these areas. Since an 8-hole injector design is adopted and the nozzle spacing is evenly distributed, a 1/8 combustion chamber model is adopted. The combustion chamber model is shown in Figure 2. This study primarily investigates the atomization and combustion processes of diesel, and thus, the model was simplified accordingly. In the three-dimensional CFD calculations, the computational domain was defined as the closed region between the intake valve closing (-124 °CA ATDC) and the exhaust valve opening (132 °CA ATDC), to simulate the in-cylinder flow field and chemical reaction characteristics during actual combustion. The engine speed was maintained at 2000 r/min, with intake pressure set at 0.25 MPa and intake temperature at 373 K.

Figure 1.The schematic system of engine.

Figure 2.CFD grid model.

Selecting appropriate physical and chemical models is crucial for ensuring the accuracy of combustion process simulations. In terms of turbulence modeling, the Renormalization Group (RNG) k-ε turbulence model [25] was adopted in this study. This model effectively captures the flow characteristics in low Reynolds number regions and demonstrates high accuracy and stability in complex shear flows and vortex scales. In terms of droplet dynamics modeling, in order to accurately describe the collision behavior between droplets and their interaction with the wall during the spray process, the NTC collision model [26] and the O’Rourke model [27] were used for joint modeling. The droplet evaporation process was modeled using the Frossling model [28], which is based on heat and mass transfer theory and can effectively predict the evaporation rate of droplets in different temperature fields. The Kelvin-Helmholtz/Rayleigh-Taylor (KH-RT) model [29] is used to simulate the spray breakup process. This model effectively captures both primary and secondary breakup mechanisms, making it one of the most mature spray modeling methods in current CFD applications. In terms of chemical reactions, the SAGE combustion model [30] is employed, coupling detailed chemical reaction mechanisms to simulate the in-cylinder combustion process of a methanol/n-heptane blended fuel. The adopted kinetic mechanism includes 52 species and 182 reaction steps [31]. Additionally, for pollutant formation, the Extended Zeldovich mechanism is used to predict the generation of NO_x, while the Hiroyasu-NSC soot model is applied to describe the formation and oxidation behavior of soot particles.

2.2.Model Validation

The mesh size has a significant impact on the computational efficiency and prediction accuracy of CFD simulations. Larger meshes can increase the computational speed, but it is often difficult to accurately capture key flow characteristics and combustion details. Although too fine a mesh is conducive to improving accuracy, it will significantly increase the computational cost. Therefore, under the premise of ensuring the accuracy of the simulation results, it is particularly important to reasonably select the basic mesh size to balance accuracy and computational efficiency. In order to verify the sensitivity of the simulation results to the mesh size, this paper uses three basic mesh scales, namely coarse mesh (5 mm), medium mesh (4 mm), and fine mesh (3 mm), to carry out mesh independence analysis. Figure 3 shows a comparison of in-cylinder pressure under three different grid conditions. As shown in Figure 3, when the base grid size is 4 mm, further mesh refinement has a negligible impact on in-cylinder combustion. Considering both accuracy and computational efficiency, a 4 mm base grid size is selected for subsequent simulations. Structured hexahedral meshes are automatically generated using CONVERGE software (Version 3.1, Convergent Science, Inc., Madison, WI, USA), incorporating adaptive refinement based on the base grid size and a fixed-area refinement strategy. During the injection duration, mesh refinement is applied to the fuel spray region using a three-level refinement strategy, with the minimum grid size set to 0.5 mm.

Figure 3.Verification of the sensitivity of the basic grid size.

Figure 4 shows the effect of different methanol/diesel ratios on the in-cylinder pressure and HRR. As shown in Figure 4, with the increase of the methanol mixing ratio, the in-cylinder peak pressure and HRR both show a downward trend. Li et al. [32] showed that too high a methanol mixing ratio will lead to deterioration of combustion and cause knock. Therefore, in order to ensure the stability and safety of combustion, this paper sets the upper limit of the methanol mixing ratio to 30%. With the increase of the methanol mixing ratio, the in-cylinder peak pressure gradually decreases, and the combustion start time is delayed.

Figure 4.Comparison of test and simulation values of cylinder pressure and HRR.

3.1.Effect of Methanol/Diesel Ratio on Engine Cylinder Pressure

Figure 5 shows the effect of different methanol/diesel blending ratios on in-cylinder pressure. As shown in Figure 5, the maximum in-cylinder pressure gradually decreases with the increasing methanol blend ratio. At M30/D70, the maximum in-cylinder pressure is 11.79 MPa, which represents a 15.22% decrease compared to the M0/D100. This can be attributed to the fact that the heating value of methanol is only 46.26% that of diesel, which is significantly lower. As the methanol blend ratio increases, the overall heating value and energy content of the fuel mixture decrease, leading to less energy being released during combustion. This reduction in energy results in lower in-cylinder pressure.

Figure 5.Effect of methanol blending ratio on cylinder pressure.

3.2.Effect of Methanol/Diesel Ratio on Engine Cylinder Temperature

Figure 6 shows the effect of different methanol/diesel blending ratios on in-cylinder temperature. As shown in Figure 6, the peak in-cylinder temperature gradually decreases with an increasing methanol blend ratio. At M30/D70, the peak in-cylinder temperature is reduced by 11.71% compared to the M0/D100. This can be attributed to the higher vaporization latent heat of methanol compared to diesel. Increasing the methanol ratio requires more heat for the vaporization of the methanol/diesel fuel mixture. When methanol is blended with diesel, it not only lowers the compression temperature but also reduces the combustion temperature. Furthermore, the lower heating value of methanol, which is less than half that of diesel, results in a reduced amount of heat released during the combustion process, further decreasing the in-cylinder temperature.

Figure 6.Effect of methanol blending ratio on cylinder temperature.

3.3.Effect of Methanol/Diesel Ratio on Engine Emission Performance

Figure 7 shows the effect of different methanol/diesel mixing ratios on NO_x emissions. As shown in Figure 7, as the methanol mixing ratio increases, the NO_x emission concentration in the engine exhaust gradually decreases. At M30/D70, the NO_x emission concentration reaches the lowest value, which is 41.12% lower than that of M0/D100. This is because methanol has a higher latent heat of vaporization. After mixing with methanol, the engine intake temperature and combustion temperature are both reduced, thereby reducing the generation of NO_x.

Figure 7.Effect of methanol blending ratio on NO_x.

Figure 8 shows the effect of different methanol/diesel blend ratios on NO emissions. As shown in Figure 8, NO emissions decrease significantly with an increase in the methanol blend ratio. At M30/D70, NO emissions reach their lowest point, showing a 66.96% reduction compared to the M0/D100. The formation of NO is highly dependent on the localized high-temperature environment during combustion, particularly the peak temperature and the duration of high temperatures. Methanol, with its high latent heat of vaporization, absorbs a considerable amount of heat during the initial vaporization stage, which results in a reduction in peak in-cylinder temperature and a shorter duration of high temperatures. This process effectively suppresses the formation of thermal NO. Furthermore, since methanol does not contain nitrogen, the overall nitrogen-containing components participating in the combustion reaction decrease, further reducing the potential for NO formation.

Figure 8.Effect of methanol blending ratio on NO.

Figure 9 shows the effect of different methanol/diesel blend ratios on soot emissions. As shown in Figure 9, Soot emissions significantly decrease with an increase in the methanol blend ratio. At M30/D70, soot emissions reach their lowest level, with a 26.54% reduction compared to the M0/D100. This is due to methanol’s high latent heat of vaporization, which absorbs a significant amount of heat during the spray evaporation process, thereby lowering the local in-cylinder temperature. This reduction suppresses the formation of localized rich fuel zones, weakens the pyrolysis reactions under high-temperature, oxygen-deficient conditions, and consequently reduces soot formation. Additionally, since methanol molecules lack C–C bonds, the formation of polycyclic aromatic hydrocarbons and other soot precursors is limited during combustion, effectively inhibiting the soot formation pathway. Therefore, with an increase in the methanol blend ratio, the combustion process becomes cleaner, leading to a significant reduction in soot emissions.

Figure 9.Effect of methanol blending ratio on soot.

Figure 10 shows the effect of different methanol/diesel blending ratios on CO emissions. As shown in Figure 10, as the methanol blending ratio increases, CO emissions show a clear upward trend. At M30/D70, the CO emission concentration reaches a peak, which is 44.23 times higher than that of M0/D100. Since methanol is a low-carbon fuel, increasing the methanol blending ratio will lead to an increase in the carbon content of the mixed fuel. Therefore, as the methanol blending ratio increases, the CO emission concentration in the engine exhaust gas gradually increases. When the methanol blending ratio reaches 30%, the CO emission concentration reaches the highest value. The main reason for this phenomenon is that the oxidation reaction of CO requires the participation of active OH radicals, and the addition of methanol will convert some active OH radicals into inactive H₂O₂, which will lead to a decrease in the CO oxidation rate, thereby increasing CO emissions.

Figure 10.Effect of methanol blending ratio on CO.