Print Email Facebook Twitter A Conceptual aircraft design methodology for parallel hybrid-electric powertrains Title A Conceptual aircraft design methodology for parallel hybrid-electric powertrains: Prediction of engine performance and electric component integration Author Kaminski, Jonas (TU Delft Aerospace Engineering) Contributor Vos, Roelof (mentor) Hoogreef, M.F.M. (mentor) Silberhorn, Daniel (mentor) Degree granting institution Delft University of Technology Date 2022-08-12 Abstract The demand for environmentally friendly aviation has increased the interest in alternative concepts, such as hybrid-electric propulsion systems. A novel conceptual hybrid-electric sizing methodology was devised, which provides a detailed engine performance prediction and an accurate sizing of the powertrain components. The performance prediction methodology individually scales user-provided origin fan and engine core performance maps to generate a coherent engine performance map according to prescribed point performance requirements, while the component sizing methodology estimates individual component masses and determines their positions based on defined knowledge-rules. For each methodology, a dedicated design tool was created for easy integration into conceptual design workflows. A verification of the methodology via case studies assessing generated example aircraft concepts confirmed not only the validity of the obtained results, but also demonstrated a high accuracy at low computational costs. The exhibited robustness and sensitivity encourage the use of the methodology for future studies on hybrid-electric propulsion. Subject conceptual designhybrid-electric propulsionengine performance predictionelectric component sizingHEPHEPSBattery electric aircraft To reference this document use: http://resolver.tudelft.nl/uuid:a79fc268-5235-4c68-b909-ede4970524bd Part of collection Student theses Document type master thesis Rights © 2022 Jonas Kaminski Files PDF MSc_ThesisReport_JonasKaminski.pdf 7.02 MB Close viewer /islandora/object/uuid:a79fc268-5235-4c68-b909-ede4970524bd/datastream/OBJ/view