A Combined Experimental and Computational Fluid Dynamics Investigation of Particulate Matter Emissions from a Wall-Guided Gasoline Direct Injection Engine
Abstract
:1. Introduction
1.1. Particulate Matter Formation Process
- Oxidation and/or pyrolysis of fuel under fuel-rich conditions and temperature between 1000 and 2800 K;
- Production of precursor molecules from hydrocarbons species, leading to the formation of polycyclic aromatic hydrocarbons (PAH) gas species molecules;
- Polymerization of hydrocarbon rings;
- Particle inception or nucleation, as a result of the interaction between polymerized structures;
- Particles growth due to interactions between PAH species and particle surface;
- Coagulation of particles due to collision;
- Oxidation of particles in the presence of oxygen species (O2, OH, CO2, H2O) in high temperature environment (during and post combustion).
1.2. Influence of Engine Control Parameters
1.3. Influence of Combustion Parameters
1.4. Computational Fluid Dynamics Analysis of Mixture Preparation
2. Experimental Setup and Methodology
Computational Fluid Dynamics Modelling
3. Results and Discussion
3.1. Particulate Matter Characterisation
3.2. Apparent Correlation with Gas Temperature
3.3. Correlation between Charge Homogeneity and Particle Number Density
4. Conclusions
- The analysis of size-resolved particle number density distributions reveals a mostly bi-modal functional form, featuring much greater levels in nucleation mode (<50 nm). In the lowest sooting conditions (engine load of 120 Nm and speed of 3600 rpm and above), the distributions present mono-modal form with peak located at the high end of nucleation mode interval.
- Increases in engine speed and load lead to lower particle number densities and larger size. The effect of engine load is more pronounced and results from greater injection pressure which improves charge homogeneity through better fuel atomisation.
- The total PNDen varies between 1.7 × 107 and 4.0 × 105 particles/cm3, showing larger dependence on engine speed at low load and lower dependence at higher load. The results suggest that both improved mixture preparation and lower peak combustion temperature contribute to the reduction in particle number concentration as engine speed and load increase.
- The GMD varies between 10 and 60 nm. Conversely to PNDen, GMD shows low dependence on engine speed at low load and greater dependence at higher load. Stronger particle coagulation and lower oxidation may contribute to greater particle size as engine speed and load increase.
- 72% of particles are emitted on average in the 5–23 nm size range, while over 80% falls in the nucleation mode range. Only 10% of particles are emitted in accumulation mode (51–100 nm). The very high frequencies in the sub-23 nm range expose potential limitations of the incoming EU6c/d emission regulations, which do not consider particles below this threshold.
- The volume-based uniformity index of equivalence ratio (UIφ) was calculated through a limited number of CFD simulations of the test-engine, and used as an indication of the effectiveness of the mixture preparation process. A strong power-law type correlation exists between PNDen and UIφ calculated at spark timing. Relatively small increases in charge homogeneity of the order of 6% are associated to large reductions of total particle number density of approximately one order of magnitude.
- A strong correlation can also be identified between PNDen and modelled ideal-gas temperature at the location of peak combustion pressure. Reducing temperature between 2650 K and 2150 K would lead, dependent on engine running conditions, to a three to five-fold increase in average size, as well as to 90% reduction in total number density.
- A simple two-equation functional model was developed which returns satisfactory qualitative predictions of total PNDen as a function of basic engine control variables. The initial model is unsophisticated and requires engine-specific calibration and further improvement; nevertheless, the approach identifies a potential effective route to perform real-time control of soot number output in modern GDI engines. Future work by the Authors will focus on improving this model and explore further potential correlations existing between engine varibales and average particle size.
Author Contributions
Conflicts of Interest
Nomenclature
AFR | Air Fuel Ratio |
ATDC | After Top Dead Centre |
BDC | Bottom Dead Centre |
BMEP | Brake Mean Effective Pressure |
BTDC | Before Top Death Centre |
CA | Crank Angle |
CF | Conformity Factors |
CFD | Computational Fluid Dynamics |
DMS | Differential Mobility Spectrometer |
ECU | Engine Control Unit |
EGR | Exhaust Gas Recirculation |
EOI | End of Injection |
EU | European Union |
FMS | Fuel Measurement System |
GDI | Gasoline Direct Injection |
GMD | Geometrical Mean Diameter |
GPF | Gasoline Particulate Filters |
IMEP | Indicated Mean Effective Pressure |
IVO | Intake Valve Opening |
PAH | Polycyclic Aromatic Hydrocarbons |
PEMS | Portable Emission Measuring System |
PM | Particulate Matter |
PMP | Particle Measurement Programme |
PNDen | Particle Number Density |
RDE | Real Driving Emission |
RMSE | Root Mean Square Error |
RON | Research Octane Number |
SMD | Sauter Mean Diameter |
SOI | Start of Injection |
ST | Spark Timing |
TDC | Top Dead Centre |
uHC | Unburned Hydrocarbons |
UIϕ | Uniformity Index of Equivalence Ratio |
VVT | Variable Valve Timing |
WLTC | Worldwide Harmonized Light Duty Vehicles Test Cycle |
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Characteristic | Units | Value/Description |
---|---|---|
Bore | mm | 77 |
Stroke | mm | 85.8 |
Compression ratio | - | 10.5:1 |
Connecting Rod Length | mm | 138.4 |
Combustion chamber | - | 4-Valve, central spark plug, pent-roof design |
Engine type | - | In-line 4-cylinder |
Cycle | - | 4-Stroke spark ignition |
Fuel injector system | - | Direct injection common rail |
Fuel injectors | - | Side-mounted, wall-guided spray |
Maximum injection pressure | bar | 120 |
Characteristic/Component | Units | Min | Max |
---|---|---|---|
RON | - | 95 | - |
MON | - | 85 | - |
Aromatics | vol % | 29 | 35 |
Olefins | vol % | 3 | 13 |
Saturates | vol % | - | - |
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Sciortino, D.D.; Bonatesta, F.; Hopkins, E.; Yang, C.; Morrey, D. A Combined Experimental and Computational Fluid Dynamics Investigation of Particulate Matter Emissions from a Wall-Guided Gasoline Direct Injection Engine. Energies 2017, 10, 1408. https://doi.org/10.3390/en10091408
Sciortino DD, Bonatesta F, Hopkins E, Yang C, Morrey D. A Combined Experimental and Computational Fluid Dynamics Investigation of Particulate Matter Emissions from a Wall-Guided Gasoline Direct Injection Engine. Energies. 2017; 10(9):1408. https://doi.org/10.3390/en10091408
Chicago/Turabian StyleSciortino, Davide D., Fabrizio Bonatesta, Edward Hopkins, Changho Yang, and Denise Morrey. 2017. "A Combined Experimental and Computational Fluid Dynamics Investigation of Particulate Matter Emissions from a Wall-Guided Gasoline Direct Injection Engine" Energies 10, no. 9: 1408. https://doi.org/10.3390/en10091408