Multi-Dimensional Engine Modeling Study of EGR, Fuel Pressure, Post-Injection and Compression Ratio for a Light Duty Diesel Engine
Bibliographic record
Abstract
For copious levels of exhaust gas recirculation (EGR) (>30 %), oxides of nitrogen (NOx) emissions can be reduced from Euro V to Euro VI regulated levels at the expense of fuel economy and soot emissions. The Lifted-Flame Concept (LFC) has been demonstrated by several researchers to be successful in reducing NOx, while minimizing soot emissions and impact to fuel economy. By simultaneously applying increased EGR and fuel pressure the LFC extends the lift-off length of a diffusion flame and enhances fuel-air entrainment leading to improved fuel and oxygen utilization. When combined with advanced turbocharging and EGR systems the LFC applied to a modern light duty (LD) diesel engine can result in improved fuel economy and lower soot emissions and shows good potential for meeting low soot engine-out targets. In the proposed paper a computational study was conducted using a multi-dimensional engine model. A modified 3D CFD KIVA code with detailed chemistry solver was used to model the diesel fuel spray, droplet breakup, vaporization, mixing, auto-ignition and subsequent heat release and emissions. The model uses inputs from 1D Amesim electro-hydraulic solver to generate the rate of injection (ROI) profile to raise pressure of 1800 bar to 2500 bar as well as to include a simulated post-injection. A 1D model using GT-Power was developed and utilized to provide air system boundary conditions for the 3D CFD model. Post-processing optimization was conducted using Matlab to identify minimum fuel economy and soot emissions for the study of several parameters. The objective of the study was to demonstrate Euro VI emissions levels on a 3.2 L LD diesel engine without NOx aftertreatment and minimal impact to fuel economy using the lifted flame concept. The engine-out NOx emission level was targeted at 0.4 g/kWh and the soot levels were targeted at 0.2 g/kWh assuming diesel particulate filter would be used for after-treatment. The results of the computational study successfully demonstrate the potential of the lifted flame concept to meet Euro VI without the use of NOx aftertreatment technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".