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Record W4409018077 · doi:10.4271/2025-01-8404

Combustion and Emissions Improvement of Engine Idling Via Advanced Ignition Strategies

2025· article· en· W4409018077 on OpenAlexaff
Xiao Yu, Guangyun Chen, Jin-yuan Qian, Simon Leblanc, Linyan Wang, Ming Zheng

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsIgnition systemAutomotive engineeringCombustionHomogeneous charge compression ignitionEnvironmental scienceIgnition timingComputer scienceInternal combustion engineAerospace engineeringEngineeringCombustion chamberChemistry

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">During engine idling, the low engine speed, typically from 600 rpm to 800 rpm, together with the low throttle opening angle, makes it challenging for a proper fuel air mixing process. The uneven intake charge distribution and high portion of internal EGR because of the inefficient gas exchange process further make the air fuel ratio unstable, which is challenging for a robust ignition and combustion process. In this paper, the challenge of achieving proper combustion phasing while maintaining acceptable combustion stability is investigated, and a specially designed common-coil pack was utilized to improve engine idling performance by supplying prolonged ignition duration and elevated discharge current amplitude. The common-coil pack, which comprises three parallel connected ignition coils, was shared by all 4 cylinders of the engine. The ignition strategy shows the capability to advance the combustion phasing for higher IMEP output, while maintaining the combustion stability, and reduce engine out emissions.</div></div>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.250
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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