Adaptive Combustion Control to Improve Diesel HCCI Cycle Fuel Efficiency
Bibliographic record
Abstract
Previous work indicates that the lowered combustion temperature in diesel engines is capable of reducing nitrogen oxides and soot simultaneously, which can be implemented by the heavy use of exhaust gas recirculation or the homogeneous charge compression ignition (HCCI) type of combustion. However, the fuel efficiency of the low temperature combustion cycles is commonly compromised with high levels of hydrocarbon and carbon monoxide emissions. Additionally, in cases of diesel HCCI cycles, the combustion process may even occur before the piston completes the compression stroke, which may cause excessive efficiency reduction and combustion roughness. Adaptive control strategies are applied to precisely navigate and stabilize the engine cycles and to better phase and complete the combustion process. The impact of heat release phasing, duration, shaping, and splitting on the thermal efficiency has also been analyzed with zero-dimensional engine cycle simulations. The correlations between the cylinder pressure and the heat release curves have been characterized to facilitate model based control. The empirical set-up and cases of applications are provided.
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 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 | 0.001 |
| 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) | 0.000 | 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".