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Record W2031861525 · doi:10.4271/2014-01-2661

Study of Combustion Behavior and Combustion Stability of HCCI-DI Combustion for a Wide Operating Range using a Low Cost Novel Experimental Technique

2014· article· en· W2031861525 on OpenAlexfundno aff
Pranab Das, PMV Subbarao, J. P. Subrahmanyam

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsCombustionHomogeneous charge compression ignitionStability (learning theory)Range (aeronautics)Materials scienceAutomotive engineeringNuclear engineeringComputer scienceChemistryCombustion chamberEngineeringComposite material

Abstract

fetched live from OpenAlex

An innovative method is developed for achieving HCCI-DI combustion without any major engine geometry modification. Many control strategies have been reported in literature, in spite of that even today no HCCI combustion engine is available on commercial basis. Pilot and main fuel injection strategy is used as a control strategy in this work. Our developed technique is a low cost alternative to conventional CRDI pumps which can be implemented readily at least for rural application engines (where cost of the system is more important than any other aspects) to reduce emissions. Using this new technique a stable HCCI-DI combustion was achieved for a wide operating range. To realize the effectiveness of this developed experimentation technique, a detailed combustion study at various operating conditions were investigated using commercial diesel as fuel. Pilot injection timing was fixed at 270 degrees bTDC allowing sufficient time for homogeneous mixture preparation and main injection was fixed at 26 degrees bTDC to trigger the combustion. Split ratio was varied from zero to 95% at various operating load (2 bar Net IMEP to 6.5 bar Net IMEP) conditions. This study is limited up to 95% split ratio since the engine went beyond drivability limit (COV of IMEP <10% as defined in Stone, 2012 [10]) with 100% split ratio in most of the operating conditions. The behavior of all combustion parameters (cylinder pressure, pressure rise rate, heat release rate and start of combustion) at various operating conditions are analyzed and presented in this paper. It was evident from the results that with increasing split ratio, all combustion parameters start advancing. Similarly, at any constant split ratio all combustion parameters started advancing with increasing load. Cycle by cycle statistical analysis of peak cycle pressure and net IMEP for 100 consecutive cycles is also analyzed to understand the combustion stability achieved using this technique. In HCCI combustion, low load limit is widely defined by high value of COV of IMEP and High load limit is defined by knocking combustion. This study shows, even at a 95% split ratio and at very low intake air temperature, cycle by cycle variation was found within drivability limit and therefore, No misfire region exists even at idling (2 bar IMEP) condition. Therefore, extreme Low load range can be achieved using a combination of pilot and main injection strategy. Combustion stability at various split ratio and load were also compared with conventional diesel combustion. Ringing Index (RI) is calculated to find the high load limit of HCCI-DI combustion of the modified engine. It is found that RI monotonically increased with increasing split ratio and increasing load. At higher split ratio, RI is extremely sensitive to engine load. At 80% split ratio and at 6.5 bar IMEP condition, RI was found to be 8 times higher than the corresponding baseline combustion. At higher split ratio, high load range narrows down. To increase load range, split ratio should be reduced if no other control strategy is used.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.291
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2014
Admission routes1
Has abstractyes

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