Hydrogen fuel cell integration and testing in a hybrid-electric propulsion rig
Bibliographic record
Abstract
On the road towards greener aviation, hybrid-electric propulsion systems have emerged as a viable solution. In this paper, a system based on hydrogen fuel cells is proposed and evaluated in a laboratory setting with its future integration in a propulsive system in mind and main focus on the ability to lessen the power demand on the opposing side of the bench. The setup consists in a parallel architecture with two power sources: a hydrogen fuel cell and a battery. First, the performance of the fuel cell and its capability to provide power to one of the motors are analyzed. Then, the entire parallel hybrid system is evaluated. Although the experimental setup was shown to be sub-optimal, the results demonstrated the ability of this greener alternative to reduce power demand on the opposing side of the parallel configuration, with a reduction of up to 40.3% in the highest load scenario, and maximum power output on the fuel cell of 257.8 W. The stack performance was also concluded to be very dependent on the operating temperature.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".