Real-Time Monitoring of Combustion Instability in a Homogeneous Charge Compression Ignition (HCCI) Engine Using Cycle-by-Cycle Exhaust Temperature Measurements
Bibliographic record
Abstract
This paper describes an experimental study concerning the feasibility of monitoring the combustion instability levels of an HCCI engine based upon cycle-by-cycle exhaust temperature measurements. The test engine was a single cylinder, four-stroke, variable compression ratio Cooperative Fuel Research (CFR) engine coupled to an eddy current dynamometer. A rugged exhaust temperature sensor equipped with special signal processing circuitry was installed near the engine exhaust port. Reference measurements were provided by a laboratory grade, water-cooled cylinder pressure transducer. The cylinder pressure measurements were used to calculate the Coefficient of Variation of Indicated Mean Effective Pressure (COV of IMEP) for each operating condition tested. Experiments with the HCCI engine confirmed that cycle-by-cycle variations in exhaust temperature were present, and were of sufficient magnitude to be captured for processing as high fidelity signal waveforms. There was a good correlation between the variability of the exhaust temperature signal and the COV of IMEP throughout the operating range that was evaluated. The correlation was particularly strong at the low levels of COV of IMEP (2–3%), where production engines would typically operate. A real-time combustion instability signal was obtained from cycle-by-cycle exhaust temperature measurements, and used to provide feedback to the fuel injection control system. Closed loop operation of the HCCI engine was achieved in which the engine was operated as lean as possible while maintaining the COV level at or near 2.5%.
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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 | 0.000 |
| 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".