Optimum sub-megawatt electric-hybrid power source selection
Bibliographic record
Abstract
Purpose The limited energy density of batteries generates the need for high-performance power sources for emerging eVTOL applications with radical operational improvement potential over traditional aircraft. This paper aims to evaluate on-design and off-design recuperated turbogenerator performances based on newly developed compression loaded ceramic turbines, the Inside-out Ceramic Turbine (ICT), in order to select the optimum engine configuration for sub-megawatt systems. Design/methodology/approach System-level thermal engine modeling is combined with electric generators and power electronics performance predictions to obtain the Pareto front between efficiency and power density for a variety of engine designs, both for recuperated and simple cycle turbines. Part load efficiency for those engines are evaluated, and the results are used for an engine selection based on a simplified eVTOL mission capability. Findings By operating with high turbine inlet temperature, variable output speed and adequately sized recuperator, a turbogenerator provides exceptional efficiency at both nominal power and part load operation for a turbomachine, while maintaining the high power density required for aircraft. In application with a high peak-to-cruise power ratio, such power source would provide eight times the range of battery-electric power pack and an 80% improvement over the state-of-the-art simple cycle turbogenerator. Practical implications The implementation of a recuperator would provide additional gains especially important for military and on-demand mobility applications, notably reducing the heat signature and noise of the system. The engine low-pressure ratio reduces its complexity and combined with the fuel savings, the system could significantly reduce operational cost. Originality/value Implementation of radically new ICT architecture provides the key element to make a sub-megawatt recuperated turbogenerator viable in terms of power density. The synergetic combination of a recuperator, high temperature turbine and variable speed electric generator provides drastic improvement over simple-cycle turbines, making such a system highly relevant as the power source for future eVTOL applications.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".