Recently, the new Green Deal policy initiative was presented by the European Union. The EU aims to achieve a sustainable future and be the first climate-neutral continent by 2050. It targets all of the continent’s industries, meaning aviation must contribute to these changes as well. By employing a systems engineering approach, this high-level task can be split into different levels to get from the vision to the relevant system or product itself. Part of this iterative process involves the aircraft requirements, which make the goals more achievable on the system level and allow validation of whether the designed systems fulfill these requirements. Within this work, the top-level aircraft requirements (TLARs) for a hybrid-electric regional aircraft for up to 50 passengers are presented. Apart from performance requirements, other requirements, like environmental ones, are also included. To check whether these requirements are fulfilled, different reference missions were defined which challenge various extremes within the requirements. Furthermore, figures of merit are established, providing a way of validating and comparing different aircraft designs. The modular structure of these aircraft designs ensures the possibility of evaluating different architectures and adapting these figures if necessary. Moreover, different criteria can be accounted for, or their calculation methods or weighting can be changed.

In the wake of many climate-friendly initiatives, the aviation sector must become more sustainable. A potential path for regional airliners could be the installation of hybrid-electric powertrains. In this work, a conceptual study design of various powertrain architectures is conducted. This helps the designer to quickly generate approximate numbers on the basic characteristics of new aircraft configurations. These results can be used to advance subsystems modeling or improve the starting values in the following preliminary aircraft design. After the selection of representative architectures, reasonable technological assumptions were gathered, ranging between a conservative and an optimistic scenario. This was done for powertrain components, various energy storage concepts and structural and aerodynamic changes. The initial sizing method was developed by building two interconnected sizing iteration loops. In addition, a safety assessment was integrated due to the many unconventional components in the powertrain’s setup. The results show that the fuel consumption of a conventional aircraft is not undercut with a hybrid-electric powertrain aircraft based on conservative technological assumptions. In the optimistic scenario, however, selected powertrain architectures show a significant drop in fuel consumption when compared to the conventional one. Furthermore, the use of synergistic effects and systematic powertrain optimizations can decrease the fuel consumption even further. In conclusion, it was shown that this initial sizing method can calculate entire hybrid-electric aircraft designs on a conceptual level. The results can quickly present trends that are reasonable and helpful. In addition, the safety assessment first gives evidence about which levels of safety have to be considered for the different components in the development of hybrid-electric powertrains.

A hybrid-electric regional aircraft for 50 passengers has challenges in technology, operation and future regulations similar to larger class aircraft. It is thus at the right spot to drive technology, regulations and operational developments in order to accelerate cleaner flight technologies based on propulsion electrification. The FutPrInt50 team set up Top-Level Aircraft Requirements that aim to be a reference foundation for the development of specific topics handled in this H2020 project but also drive the open collaboration model adopted by FutPrInt50. In this paper the development of the mission statement will be explained for a hybrid-electric 50 passenger regional aircraft, which builds the framework for the Top-Level Aircraft Requirements. To further support development from these requirements, a mission scenario will be presented for this class of aircraft.

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.

New, highly integrated, disruptive aircraft concepts are being devised to reduce aviation’s environmental footprint, but their performance is oftentimes challenging for the aircraft designer to assess. Furthermore, these novel aircraft often introduce new risks, such as noise, that cannot be addressed quickly by available methods. Overall, in the pursuit of more environmental friendly aircraft configurations and the lack of methods to design such aircraft, aircraft-level trade-offs between noise and performance are challenging. The present study aims to close this gap by using a machine learning-based approach for one unconventional aircraft to investigate usability in the early stages of aircraft design. Based on overflight noise measurements, noise models for this aircraft are created with different approaches and base models. The single-output models show good performance, with mean absolute errors around 1 dB, good rank correlations and R² scores above 0.9. Support vector regression provides reasonably good agreement from experiments requiring only a small effort to set up; Neural Networks achieve better performance, but increased effort is required to obtain the model.