Fuel consumption evaluation of an optimized new hybrid pneumatic–combustion vehicle engine on several driving cycles
Bibliographic record
Abstract
In this paper, we describe an optimization followed by a fuel-saving evaluation of a new concept of a hybrid pneumatic–combustion engine that can be obtained by modifying a conventional internal combustion engine without developing a new cylinder head. Until now, most studies on the pneumatic hybridization of internal combustion engines have dealt with a two-stroke pure pneumatic mode. The few concept studies that have dealt with a hybrid pneumatic–combustion four-stroke mode required a supplementary valve to be added to charge compressed air in the combustion chamber. This heavy modification cannot be carried out by simply adjusting an existing internal combustion engine because a new cylinder head should be developed. It is therefore not logical to suggest this concept as an option in vehicle powertrains to reduce fuel consumption. Moreover, those studies focus on spark-ignition engines; there are reasons to think that their concepts might not work adequately for diesel engines. Our concept is capable of making a diesel engine operate under two-stroke pneumatic motor modes, two-stroke pneumatic pump modes and four-stroke hybrid modes, without requiring an additional valve in the combustion chamber. This fact constitutes our study’s strength and innovation. The evaluation of our concept is based on ideal thermodynamic cycle modeling. The optimized valve actuation timings for all modes lead to generic maps that are independent of the engine size. The fuel economy is calculated based on the new European driving cycle and on the assessment and reliability of transport emission models and inventory system urban and rural cycles.
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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 | 0.001 | 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".