@article{Dachwald2005,
  author    = {Dachwald, Bernd},
  title     = {Optimization of very-low-thrust trajectories using evolutionary neurocontrol},
  series = {Acta Astronautica},
  volume    = {57},
  journal   = {Acta Astronautica},
  number    = {2-8},
  publisher = {Elsevier},
  address   = {Amsterdam [u.a.]},
  isbn      = {1879-2030},
  pages     = {175 -- 185},
  year      = {2005},
  abstract  = {Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).},
  language  = {en}
}
@article{PeloniCeriottiDachwald2016,
  author    = {Peloni, Alessandro and Ceriotti, Matteo and Dachwald, Bernd},
  title     = {Solar-sail trajectory design for a multiple near-earth-asteroid rendezvous mission},
  series = {Journal of Guidance, Control, and Dynamics},
  volume    = {39},
  journal   = {Journal of Guidance, Control, and Dynamics},
  number    = {12},
  publisher = {AIAA},
  address   = {Reston, Va.},
  issn      = {0731-5090},
  doi       = {10.2514/1.G000470},
  pages     = {2712 -- 2724},
  year      = {2016},
  abstract  = {The scientific interest for near-Earth asteroids as well as the interest in potentially hazardous asteroids from the perspective of planetary defense led the space community to focus on near-Earth asteroid mission studies. A multiple near-Earth asteroid rendezvous mission with close-up observations of several objects can help to improve the characterization of these asteroids. This work explores the design of a solar-sail spacecraft for such a mission, focusing on the search of possible sequences of encounters and the trajectory optimization. This is done in two sequential steps: a sequence search by means of a simplified trajectory model and a set of heuristic rules based on astrodynamics, and a subsequent optimization phase. A shape-based approach for solar sailing has been developed and is used for the first phase. The effectiveness of the proposed approach is demonstrated through a fully optimized multiple near-Earth asteroid rendezvous mission. The results show that it is possible to visit five near-Earth asteroids within 10 years with near-term solar-sail technology.},
  language  = {en}
}
@article{HammerQuitterMayntzetal.2023,
  author    = {Hammer, Thorben and Quitter, Julius and Mayntz, Joscha and Bauschat, J.-Michael and Dahmann, Peter and G{\"o}tten, Falk and Hille, S. and Stumpf, E.},
  title     = {Free fall drag estimation of small-scale multirotor unmanned aircraft systems using computational fluid dynamics and wind tunnel experiments},
  series = {CEAS Aeronautical Journal},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer},
  address   = {Wien},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-023-00702-w},
  pages     = {14 Seiten},
  year      = {2023},
  abstract  = {New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier-Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110\%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40\% up to 85\%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments.},
  language  = {en}
}
@article{KochBoehnischVerdoncketal.2024,
  author    = {Koch, Christopher and B{\"o}hnisch, Nils and Verdonck, Hendrik and Hach, Oliver and Braun, Carsten},
  title     = {Comparison of unsteady low- and mid-fidelity propeller aerodynamic methods for whirl flutter applications},
  series = {Applied Sciences},
  volume    = {14},
  journal   = {Applied Sciences},
  number    = {2},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2076-3417},
  doi       = {10.3390/app14020850},
  pages     = {1 -- 28},
  year      = {2024},
  abstract  = {Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.},
  language  = {en}
}
@article{FunkeEschRoosen2022,
  author    = {Funke, Harald and Esch, Thomas and Roosen, Petra},
  title     = {Powertrain Adaptions for LPG Usage in General Aviation},
  series = {MTZ worldwide},
  volume    = {2022},
  journal   = {MTZ worldwide},
  number    = {83},
  publisher = {Springer Nature},
  address   = {Basel},
  doi       = {10.1007/s38313-021-0756-6},
  pages     = {58 -- 62},
  year      = {2022},
  abstract  = {In general aviation, too, it is desirable to be able to operate existing internal combustion engines with fuels that produce less CO₂ than Avgas 100LL being widely used today It can be assumed that, in comparison, the fuels CNG, LPG or LNG, which are gaseous under normal conditions, produce significantly lower emissions. Necessary propulsion system adaptations were investigated as part of a research project at Aachen University of Applied Sciences.},
  language  = {en}
}
@article{LaarmannThomaMischetal.2023,
  author    = {Laarmann, Lukas and Thoma, Andreas and Misch, Philipp and R{\"o}th, Thilo and Braun, Carsten and Watkins, Simon and Fard, Mohammad},
  title     = {Automotive safety approach for future eVTOL vehicles},
  series = {CEAS Aeronautical Journal},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer Nature},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-023-00655-0},
  pages     = {11 Seiten},
  year      = {2023},
  abstract  = {The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL's crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.},
  language  = {en}
}
@article{SchulzeFeyerlPischinger2023,
  author    = {Schulze, Sven and Feyerl, G{\"u}nter and Pischinger, Stefan},
  title     = {Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions},
  series = {Energies},
  volume    = {16},
  journal   = {Energies},
  number    = {13},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1996-1073},
  doi       = {10.3390/en16135171},
  pages     = {29 Seiten, Art. Nr.: 5171},
  year      = {2023},
  abstract  = {To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15\% more efficiently by 2025 and 30\% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2\% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.},
  language  = {en}
}
@article{Esch2010,
  author    = {Esch, Thomas},
  title     = {Trends in commercial vehicle powertrains},
  series = {ATZautotechnology},
  volume    = {2010},
  journal   = {ATZautotechnology},
  number    = {10},
  publisher = {Vieweg \& Sohn},
  address   = {Wiesbaden},
  issn      = {2192-886X},
  doi       = {10.1007/BF03247185},
  pages     = {26 -- 31},
  year      = {2010},
  abstract  = {Low emission zones and truck bans, the rising price of diesel and increases in road tolls: all of these factors are putting serious pressure on the transport industry. Commercial vehicle manufacturers and their suppliers are in the process of identifying new solutions to these challenges as part of their efforts to meet the EEV (enhanced environmentally friendly vehicle) limits, which are currently the most robust European exhaust and emissions standards for trucks and buses.},
  language  = {en}
}
@article{FunkeEschRoosen2022,
  author    = {Funke, Harald and Esch, Thomas and Roosen, Petra},
  title     = {Antriebssystemanpassungen zur Verwendung von LPG als Flugkraftstoff},
  series = {Motortechnische Zeitschrift (MTZ)},
  volume    = {2022},
  journal   = {Motortechnische Zeitschrift (MTZ)},
  number    = {83},
  publisher = {Springer Nature},
  address   = {Basel},
  doi       = {10.1007/s35146-021-0778-2},
  pages     = {58 -- 62},
  year      = {2022},
  abstract  = {Auch in der allgemeinen Luftfahrt w{\"a}re es w{\"u}nschenswert, die bereits vorhandenen Verbrennungsmotoren mit weniger CO₂-tr{\"a}chtigen Kraftstoffen als dem heute weit verbreiteten Avgas 100LL betreiben zu k{\"o}nnen. Es ist anzunehmen, dass im Vergleich die unter Normalbedingungen gasf{\"o}rmigen Kraftstoffe CNG, LPG oder LNG deutlich weniger Emissionen produzieren. Erforderliche Antriebssystemanpassungen wurden im Rahmen eines Forschungsprojekts an der FH Aachen untersucht.},
  language  = {de}
}
@article{FayyaziSardarThomasetal.2023,
  author    = {Fayyazi, Mojgan and Sardar, Paramjotsingh and Thomas, Sumit Infent and Daghigh, Roonak and Jamali, Ali and Esch, Thomas and Kemper, Hans and Langari, Reza and Khayyam, Hamid},
  title     = {Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles},
  volume    = {15},
  number    = {6},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/su15065249},
  pages     = {38},
  year      = {2023},
  abstract  = {Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.},
  language  = {en}
}