Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment
To tackle climate change, aircraft designers envision new aircraft concepts which promise to reduce greenhouse gas emissions and enable greener flights. One option is hybrid-electric propulsion architectures. The University of Stuttgart has built and operates such an aircraft, called the e-Genius. T...
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MDPI AG
2025-05-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/12/5/401 |
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| author | Dominik Eisenhut Andreas Bender Niclas Grüning Jonas Mangold Andreas Strohmayer |
| author_facet | Dominik Eisenhut Andreas Bender Niclas Grüning Jonas Mangold Andreas Strohmayer |
| author_sort | Dominik Eisenhut |
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| description | To tackle climate change, aircraft designers envision new aircraft concepts which promise to reduce greenhouse gas emissions and enable greener flights. One option is hybrid-electric propulsion architectures. The University of Stuttgart has built and operates such an aircraft, called the e-Genius. This paper aims to demonstrate how far a digital twin is able to replicate a real-world flight using a simplified mission definition and to estimate the range limit for a high-performance hybrid-electric aircraft, lifting the operational constraints faced in the real-world environment. First a digital twin is built and compared to actual flight data to calibrate the model. Next, a comparison with a full flight is performed, using a long-range flight of 2000 km for this purpose. Due to the duration of this flight, weather conditions like wind need to be considered. Validation is performed by comparison to two additional missions, one 500 km mission flown at faster speed and a 1000 km mission flown at a similar speed. To estimate the maximum range based on this calibrated model, operational constraints like daylight and maximum flight time are lifted to see the further potential of the aircraft. This allows the aircraft to fly more slowly, at best cruise speed, and thus estimate the maximum range of the aircraft. Results show good agreement with flight tests for fuel burnt, highlighting however a need to measure additional parameters in future flights. Overall, the model allows us to plan future flights and assess the feasibility of new projects. |
| format | Article |
| id | doaj-art-d0f3eb41bab44289870072923747eaf9 |
| institution | Kabale University |
| issn | 2226-4310 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Aerospace |
| spelling | doaj-art-d0f3eb41bab44289870072923747eaf92025-08-20T03:47:49ZengMDPI AGAerospace2226-43102025-05-0112540110.3390/aerospace12050401Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design EnvironmentDominik Eisenhut0Andreas Bender1Niclas Grüning2Jonas Mangold3Andreas Strohmayer4Institute of Aircraft Design, University of Stuttgart, 70569 Stuttgart, GermanyInstitute of Aircraft Design, University of Stuttgart, 70569 Stuttgart, GermanyInstitute of Aircraft Design, University of Stuttgart, 70569 Stuttgart, GermanyInstitute of Aircraft Design, University of Stuttgart, 70569 Stuttgart, GermanyInstitute of Aircraft Design, University of Stuttgart, 70569 Stuttgart, GermanyTo tackle climate change, aircraft designers envision new aircraft concepts which promise to reduce greenhouse gas emissions and enable greener flights. One option is hybrid-electric propulsion architectures. The University of Stuttgart has built and operates such an aircraft, called the e-Genius. This paper aims to demonstrate how far a digital twin is able to replicate a real-world flight using a simplified mission definition and to estimate the range limit for a high-performance hybrid-electric aircraft, lifting the operational constraints faced in the real-world environment. First a digital twin is built and compared to actual flight data to calibrate the model. Next, a comparison with a full flight is performed, using a long-range flight of 2000 km for this purpose. Due to the duration of this flight, weather conditions like wind need to be considered. Validation is performed by comparison to two additional missions, one 500 km mission flown at faster speed and a 1000 km mission flown at a similar speed. To estimate the maximum range based on this calibrated model, operational constraints like daylight and maximum flight time are lifted to see the further potential of the aircraft. This allows the aircraft to fly more slowly, at best cruise speed, and thus estimate the maximum range of the aircraft. Results show good agreement with flight tests for fuel burnt, highlighting however a need to measure additional parameters in future flights. Overall, the model allows us to plan future flights and assess the feasibility of new projects.https://www.mdpi.com/2226-4310/12/5/401hybrid-electric aircraftaircraft designSUAVErange estimationdigital twine-Genius |
| spellingShingle | Dominik Eisenhut Andreas Bender Niclas Grüning Jonas Mangold Andreas Strohmayer Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment Aerospace hybrid-electric aircraft aircraft design SUAVE range estimation digital twin e-Genius |
| title | Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment |
| title_full | Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment |
| title_fullStr | Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment |
| title_full_unstemmed | Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment |
| title_short | Comparison of Actual Hybrid-Electric Flights with a Digital Twin in a Preliminary Aircraft Design Environment |
| title_sort | comparison of actual hybrid electric flights with a digital twin in a preliminary aircraft design environment |
| topic | hybrid-electric aircraft aircraft design SUAVE range estimation digital twin e-Genius |
| url | https://www.mdpi.com/2226-4310/12/5/401 |
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