3D CFD COMBUSTION ANALYSIS 9.1 Introduction

Converge 2.2, 3D CFD tool is used to investigate cycle to cycle variation in a gasoline direct injection engine. The GTDI engine model is modified considering the necessary boundary conditions and assumption to reduce the competition time. The boundary conditions of the model were the valve timing, spark timing, injection timing and duration, inlet pressure and temperature, exhaust pressure and temperature, intake and exhaust valve profiles, DI injector spray and targeting.

9.2 Model setup

Internal combustion engine cycle simulation includes many assumptions to set up boundary conditions to be as close as possible to the engine data from the experimental tests.

The boundary conditions used in the model are shown in table 7.5.

Setup item Values Remarks

Bore (mm) 86

Stroke (mm) 86

Connecting road length (mm) 145.5

Compression Ratio 9.2

148

Simulation Start Time (CAD) -570

Simulation End Time (CAD) 120

TDC at 0

Table 9.1, Simulation setup data for single cylinder engine cycle simulation

9.3 Model convergence

For a direct injection spark ignition engine with a turbocharging engine and valve overlaps and for internal EGR control, a 720 degree full cycle simulation is needed. In addition, it is necessary to start the cycle simulation at a time before the intake valve opens to take into consideration the trapped mass for the next cycle.

The simulation time is very important in engine cycle simulation to balance the equation between model convergence and engine cycle to cycle variation. For this investigation, we tested the simulation time that would lead to model convergence. Selecting the factor that would judge the model convergence was critical, but the overall lambda of the mixture inside the cylinder at the time just before the ignition time was the closest factor to give good results rather than keeping the simulation running for a long time to get the desired IMEP.

Lambda of 1.01-1.03 was selected as the criteria that converges after the first three to four cycles and gives stable data. All the results under different operating conditions, we ran the simulation

for 8 consecutive cycles, we ignore the first four cycles (cycle No. 1, 2, 3 and 4) to make sure the simulation converged, then we take the average of the last three to four cycles (cycle No. 5, 6, 7 and 8).

For simulating the combustion process and calculating the burning velocity to compare it with the experimental data, the last four cycles for each operating condition were post processed and the average of these four cycles was taken as the average data for calculating the burning velocity.

To investigate the effect of different parameters on the cycle to cycle variation, hundred consecutive cycles was considered for which the COV % was calculated. However, this was found to be difficult because the simulation of one cycle was found to take around 48 hours, using the available high performance computer. Finally, the model for 9 consecutive cycles and considered only the last 6 cycles.

9.4 Single cylinder and multi-cylinders engine modeling

Figure 9.1 Layout of the single cylinder engine GTDI model

While simulation of a single cylinder engine does not represent some conditions in a four cylinder engine, such as engine dynamics, intake manifold pressure and temperature fluctuation, the exhaust temperature and pressure in addition to the trapped mass, the simulation in this investigation was for one cylinder in order to get the results in a reasonable period of time. Figure 9.1 shows the 3D engine model.

150

Figure 9.2 Values of the base and simulated 1.02 Lambda (Converge CFD v2.2)

Figure 9.3 Simulated and measured IMEP around the Lambda 1.02 (Converge CFD v2.2) 0.85

Figures 9.2 and 9.3 shows the results of the CFD after calibrating the model. The desired lambda for the simulation was 1.02, and the model achieved this value after the first 4-cycles. In addition, the simulated IMEP agreed with the measured value, with.

The Pressure volume diagram of the average of the last six consecutive cycles is shown in figure 9.4. The red curve represent the P-V diagram of the average 100 consecutive cycles measured in the test cell. The blue curve represent the average of the last six consecutive cycles from the CFD simulation. The data showed a good a agreement with the experimental data.

Figure 9.4 P-V diagram for the average of the last 6-consicutive cycles. (Converge CFD v2.2) After calibrating the CFD model, the simulation ran on 1500 rpm and 15 mg of injected fuel for 10 consecutive cycles as shown in table 9.2. The first four cycles were neglected and considered to be the cycles needed for the model to adjust the boundary and initial conditions and minimize the error in the output data.

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9.5 Boundary conditions for the 3D CFD Converge model setup.

Cycle No.

Table 9.2 Boundary conditions for the 3D CFD Converge model setup.

The results showed that, even though the boundary conditions were the same for all the last 6 consecutive cycles, the simulation showed that the amount of air flow into the combustion chamber are not the same of each one of the 6 consecutive cycles as shown in figure 9.5. In addition, the results proved that the IMEP trend for the 6 consecutive cycles has the same trend as the amount of air flow.

Turbulence is a major factor in cycle to cycle variation because it affects the mixing between the fuel and air as well as the combustion process. Figure 9.6 shows the effect of tumble-X and tumble-Y on cycle to cycle variation. The results showed that the cycle to cycle variation in the GDI engine is related to the cycle average tumble ratio tumble ratio.

Figure 9.5 Effect of actual air flow in to cylinder on cycle to cycle variation. (Converge CFD v2.2) 5.24

Air In-Flow (kg) Net Ind. IMEP (bar)