Investigation of Multi-Pole Spark Ignition Under Lean Conditions and with EGR
Bibliographic record
Abstract
In order to meet the future carbon dioxide legislation, advanced clean combustion engines are tending to employ low temperature diluted combustion strategies along with intensified cylinder charge motion. The diluted mixtures are made by means of excess air admission or exhaust gas recirculation. A slower combustion speed during the early flame kernel development because of the suppressed mixture reactivity will reduce the reliability of the ignition process and the overall combustion stability. In an effort to address this issue, an ignition strategy using a multi-pole spark igniter is tested in this work. The igniter uses three electrically independent spark gaps to allow three spatially distributed spark discharges. The multi-pole spark strategy displayed more advanced combustion phasing and lower phasing variability compared to single spark discharges. Under conditions where ignition requirements are modest, both strategies could achieve comparable performance with the appropriate adjustment of spark timing. Under conditions where the ignition demands are high, such as at high EGR rates or very lean conditions, the dilution limits could be increased with the multi-pole strategy. At the low load condition tested, the lean limit could be extended from lambda 1.8 to 2. The EGR rate could similarly be extended from 26% to 32%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".