A Highly Efficient Small-Displacement Marine Two-Stroke H2DI Engine With Low Emissions
Bibliographic record
Abstract
A hydrogen-fueled two-stroke prototype demonstrator based on a 9.9 hp (7.4 kW) production gasoline marine outboard engine is presented, which, while matching the original engine's rated power output on hydrogen, achieves a best-point gross indicated thermal efficiency (ITE) of 42.4% at the ICOMIA mode 4 operating point, corresponding to 80% and 71.6% of the rated engine speed and torque, respectively. The brake thermal efficiency (BTE) at the rated power is 32.3%. Preliminary exhaust gas measurements suggest that the engine could also meet the most stringent CARB 5-Star marine spark-ignition emission standards limiting HC + NOx emissions to 2.5 g/kWh without any after-treatment. These are realized in a cost-effective concept around a proven two-stroke base engine and a low-pressure direct-injected gaseous hydrogen (LPDI GH2) system, which employs no additional fuel pump and is uniquely adapted from volume production components. Later fuel injection is found to improve thermal efficiency at the expense of increased NOx emissions and, at the extreme, increased cyclic variation. These observations are hypothesized and supported by phenomenological inferences of the observed trends of combustion duration, NOx concentration, and indicated mean effective pressure (IMEP) variance to be due to increasing charge stratification with the later timings. This work outlines the pathway—including investigations of several fuel delivery strategies with limited success—leading to the current status, including design, modeling with GT-POWER, delivery of lube oil, lubrication issues using hydrogen, and calibration sweeps. The experimental results comprising steady-state dynamometer performance, cylinder pressure traces, NOx emission measurements, along with heat release analyses, support the reported numbers and the key finding that late fuel injection timing and charge stratification drive the high efficiencies and the NOx trade-off; this is discussed and forms the basis for future work.
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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".