Impact of OEI requirement on parallel hybrid electric turboprop regional aircraft optimization
Bibliographic record
Abstract
Purpose Parallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries are depleted at the end of the mission, the hybrid powertrain designs with downsized gas turbines (GTs) and additional electric motors might not meet the one-engine inoperative (OEI) missed approach climb performance required by the certification. Alternatively, hybrid designs using the original full-size GT can perform one engine climb without electric assistance. This paper aims to evaluate the impact of overshoot climb requirements on powertrain design and performance comparing the two design approaches. Design/methodology/approach An aircraft-level parametric mission analysis model is used to evaluate aircraft performance combined with an optimization framework including multiple constraints. An indirect approach using metamodels is used to optimize powertrain sizing and operation strategy. Findings Considering OEI climb requirements, no benefits were found using a design with downsized GTs. Equivalent fuel burns were found for hybrid designs that keep the original size GTs, but do not require electric energy for the OEI overshoot at the end of the mission. Then, it is recommended to size the GT to maintain the emergency climb capabilities with no electric assistance to ensure power availability regardless of remaining battery energy. Originality/value This work introduces a new perspective on parallel HE sizing with consideration for the dependency of power capability at aircraft level on the electric energy availability in case of critical mission scenarios such as overshoot climb at the end of the mission.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".