Powertrain Design For Small Scale Parallel Hybrid-Electric Test Bench
Bibliographic record
Abstract
Abstract Parallel hybrid-electric propulsion systems for small scale unmanned aerial systems (UAS) when tested with an internal combustion engine are susceptible to damage due to increased torque compared to all-electric configurations. The University of Victoria Centre for Aerospace Research has conducted testing and identified several locations in the system for potential upgrades. One of the largest issues identified was the electromagnetic clutch’s inability to handle the torque of the Corvid-50 engine. Thus, a new clutch and powertrain system was specified which is better rated for combustion operation. Similar findings are reported based on testing performed at Ł-Institute of Aviation, where a hybrid-electric powertrain stand experienced torque spikes. The spike amplitude was several times higher than the nominal momentum of the ICE, given in the specification sheets. In result, at some working modes, a strong slippage of the clutch has been observed. It is also of highest importance to propose and test potential methods to minimize momentum influence to the powertrain. The goal is to increase robustness of such hybrid systems, and decrease the overall mass of the system.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".