Feasibility Study of a Serial Hybrid Electric Powertrain for a Light Sports Aircraft
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-2050.vid A theory-based aerodynamic model was developed and applied to electrified powertrain configurations to study the feasibility of implementing fully electric and hybrid electric technologies into light sports aircraft. Overall aircraft range was chosen as the main indicator of feasibility. The aerodynamic models were created in MATLAB/Simulink utilizing proportional-integral-derivative controllers, aerodynamic specifications of a reference aircraft body, and powertrain limitations from a physical electrified powertrain test stand. Simulations that were conducted by varying mission properties, battery properties, and fuel mass provide results which can showcase the current feasibility of electrified propulsion and make predictions for the future of the industry. Results showed that aircraft powered with a fully electric powertrain were only able to achieve 5% of the range of a traditionally powered aircraft. Aircraft using a hybrid electric powertrain were able to achieve 44% of the range of a traditionally powered aircraft, but this result was found to be almost entirely dependent on the aircraft’s fuel mass. Future predictions of Lithium-Ion battery technology are expected to increase range of fully electric aircraft to 25% of traditional, and hybrid aircraft to 60% of traditional.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it