Homogeneous charge compression ignition combustion stability improvement using a rapid ignition system
Bibliographic record
Abstract
When compared to traditional engines, homogeneous charge compression ignition has the potential to significantly reduce NO x raw emissions, while maintaining a high fuel efficiency. Homogeneous charge compression ignition is characterized by compression-induced autoignition of a lean homogeneous air–fuel mixture. Since homogeneous charge compression ignition does not utilize direct ignition control, it is strongly dependent on the state of the cylinder charge and can suffer from high cyclic variability. With spark-assisted compression ignition, it has been demonstrated that misfires can be reduced, while preserving the high thermal efficiency of homogeneous charge compression ignition as a result of the more favorable physical mixture properties due to dilution. However, spark-assisted compression ignition reduces the NO x benefits of homogeneous charge compression ignition, as it increases the local combustion temperatures. To merge the advantages of the homogeneous charge compression ignition and the spark-assisted compression ignition combustion processes, a field-programmable gate array for detailed simulation of the physical gas exchange is combined with a rapid spark system. The low latency and computational speed of the field-programmable gate array allows the simulation process to be implemented in real time. When combined with the rapid reaction time of the high-frequency current-based rapid ignition system, a feedforward controller based on the cylinder pressure or heat release is realized. The developed model-based controller determines if a spark is required to assist the homogeneous charge compression ignition combustion process. The use of the field-programmable gate array and rapid ignition system allows for the calculation of combustion properties and controller output within 0.1 °CA. This article presents the development and experimental validation of the developed controller on a single-cylinder research engine. The combustion stability has been significantly improved as reflected in an improved standard deviation of the indicated mean effective pressure and a reduction of the combustion phasing variations. Furthermore, compared to a traditional homogeneous charge compression ignition system, the hydrocarbon emissions can be reduced, while maintaining low NO x emissions.
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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 | 0.000 | 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) | 0.001 | 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".