Combustion Stability Improvement via Multiple Ignition Sites on a Production Engine
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">For spark ignition (SI) engines, further improvement of engine efficiency has become the major development trend, and lean burn/EGR technologies, as well as intensified in-cylinder flow, need to be adapted to reach that target. Stronger ignition sources become more favorable under extreme lean/EGR conditions. Among the ignition technologies developed, multiple ignition sites technology has been proved to be an effective way to help with the initial flame kernel development. In this paper, a spark ignited 4-cylinder turbo-charged production engine is employed to investigate the impact of multiple ignition sites technology on engine performance under lean burn conditions. Four in-house designed 3-core sparkplugs are installed on the cylinders to replace traditional stock sparkplugs, in order to generate multiple ignition sites in the cylinders. Under partial load, the pumping loss can be reduced when engine is running under lean conditions, so the brake engine efficiency can be improved. However, combustion stability becomes worse in terms of higher cycle to cycle variation of the engine IMEP. Compared with traditional ignition system, the multiple ignition sites technology can extend engine lean operation limit with shorter ignition delay, which can effectively reduce the cycle to cycle variation.</div></div>
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".