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https://doi.org/10.48441/4427.3286
| Title: | Generative design of hybrid-electric aircraft propulsion systems using evolutionary algorithms | Language: | English | Authors: | Albrecht, Tobias Kochan, Kay |
Keywords: | optimization; hybrid-electric propulsion; genetic algorithm; ultralight aircraft; multi-string motor | Issue Date: | 4-Dec-2025 | Project: | BeHyPSy – B4 Innovative Hydrogen Propulsion System | Conference: | CEAS Aerospace Europe Conference and AIDAA International Congress 2025 | Abstract: | The electrification of aircraft propulsion offers significant potential for emission reduction. Hydrogen-powered hybrid-electric systems combine zero carbon emissions with high energy density, enabling greater range than purely battery-electric concepts. Their tightly coupled subsystems, however, require an integrated, system-level design approach. This study presents the architectural optimisation of a hydrogen-electric multi-string propulsion system for ultralight aircraft. Power is distributed across several parallel fuel cell strings, allowing lighter air-cooling configurations. A model-based systems engineering (MBSE) framework is coupled with a genetic multi-objective optimisation algorithm to determine key sizing parameters, including the number and power of the fuel cells, as well as the energy management strategy between fuel cells and the battery. The methodology is applied to the Breezer UL B400-6 ultralight aircraft and demonstrates clear trade-offs between system mass and flight duration, offering valuable insights for early-stage design of multi-string hydrogen-electric propulsion architectures. |
URI: | https://hdl.handle.net/20.500.12738/19043 | DOI: | 10.48441/4427.3286 | Review status: | Currently there is no review planned for this version | Institute: | Fakultät Luftfahrt- und Fahrzeugsysteme | Type: | Presentation | Funded by: | Bundesministerium für Wirtschaft und Energie |
| Appears in Collections: | Publications with full text |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Presentation_CEAS25.pdf | 1.24 MB | Adobe PDF | View/Open |
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