Experimental investigation of camless air engine to improve performance by the novel controller and exhaust pressure predicting technique
Bibliographic record
Abstract
In the face of the climate crisis, hike in prices of petroleum products, and limited gasoline sources, it is imperative to explore the possible opportunities in the field of energy transformation technology. Non-conventional and non-hazardous green fuel-air engine technology has proven to have a promising future in propulsion technology. In the air engine, the camless mechanism has created scope for research by replacement option of cam-follower with variable valve train (solenoid valve), which can be controlled electronically. In this paper, work is done on the operational parameters (i.e., cycle time, flow rate, and crank position) of camless air engines and proposed a controlling mechanism with experimental results to improve the system's efficiency. Control of intake duration maximizes the utilization of input compressed air power by allowing the optimum amount of air to expand fully. The novel controller was designed, developed, and tested, which controls the engine intake duration by estimating exhaust pressure. A prototype model was built with an electronic control circuit and pneumatic system, which records signals of operational parameters with the help of feedback sensors and controls the engine's intake duration at different operating pressure ranging from 3 to 6.5 bar. Experiments were conducted, and the results of two cycles were compared, case-I, where compressed air is continuously supplied from 0° to 170° of crank angle, and case-II controlled cycle, which controls intake duration by estimating exhaust pressure. Results show the average efficiency improvement of 11.91 % in case-II compared to case-I and also improvement in work done and RPM (Revolution per Minute) of the cycle. Thus, the control system in a camless air engine increases the feasibility of the air engine as one of the propulsion technologies in a city vehicle and even in the Compressed Air Energy Storage System (CAES).
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".