An Experimental Study on the Knock Mitigation Effect of Coolant and Thermal Boundary Temperatures in Spark Ignited Engines
Bibliographic record
Abstract
Increasing compression ratio is essential for developing future high-efficiency engines due to the intrinsic characteristics of spark-ignited engines. However, it also causes the unfavorable, abnormal knocking phenomena which is the auto-ignition in the unburned end-gas region. To cope with regulations, many researchers have been experimenting with various methods to suppress knock occurrence. In this paper, it is shown that cooling the combustion chamber using coolants, which is one of the most practical methods, has a strong effect on knock mitigation. Furthermore, the relationship between thermal boundary and coolant temperatures is shown. In the beginning of this paper, knock metrics using an in-cylinder pressure sensor are explained for readers, even though entire research studies cannot be listed due to the innumerableness. The coolant passages for the cylinder head and the liner were separated to examine independent cooling strategies. In addition, piston surface temperature was changed through the oil supply to the piston oil gallery. To investigate the effects on the thermal boundary temperature under knocking conditions, temperatures were measured. Knock mitigation effects were quantified while the coolant temperatures were varied. Quantification in this study consists of two methods: The advancement of the crank angle ignition timing and the expansion of the borderline knock (detonation border line). The different impacts of cooling between PFI (port fuel injection) and GDI (gasoline direct injection) engines and the differences under various S/B (stroke-to-bore) ratios are also shown in this study. After implementation, it was shown that decreasing the coolant temperature in the cylinder head has a greater effect than that of the liner. Furthermore, 4.2 CA and 5 CA of ignition timing advance and 10% and 6.8% of knock load limit expansion were achieved while the coolant temperature was decreased from 85 °C to 60 °C under 1500 rpm and 2000 rpm, respectively. GDI engine also showed knock mitigation effects by the coolant temperature decrease. Higher stroke-to-bore ratio led to expanded load limit due to increased knock suppression. However, there was no significant difference in the effect of coolant temperature decrease for various stroke-to-bore ratios.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".