A Study on an Automatically Variable Intake Exhaust Injection Timing Turbocharging System for Diesel Engines
Bibliographic record
Abstract
Abstract A new turbocharging system, named automatically variable intake exhaust injection timing (AVIEIT), is proposed. Its main purpose is to improve the performance of low-speed high torque operating conditions and improve the economy of high-speed operating conditions for high-speed supercharged intercooled diesel engines. The principle of the AVIEIT turbocharging system is presented. A control mechanism for the proposed AVIEIT system used for a truck diesel engine is introduced. An engine simulation code has been developed. In this code, a zero-dimensional in-cylinder combustion model, a one-dimensional finite volume method-total variation diminishing model for unsteady gas flow in the intake and exhaust manifolds, and a turbocharger model are used. The developed code is used to simulate the performances of diesel engines using the AVIEIT system. Simulations of a military use diesel engine “12V150” and a truck diesel engine “D6114” using the AVIEIT system have been performed. Simulation results show that the in-cylinder charge air amount of the diesel engine with the AVIEIT system is increased at low-speed high torque operating conditions, and the fuel economy is improved at high-speed operating conditions. In order to test the idea of the AVIEIT system, an experiment on a truck diesel engine D6114 equipped with an AVIEIT control mechanism has been finished. The experiment results show that the AVIEIT system can improve the economy of high-speed operating conditions. Both the simulation and experiment results suggest that the AVIEIT system has the potential to replace the waste-gate and variable geometry turbocharger turbocharging systems.
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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".