@article{FingerBraunBil2018, author = {Finger, Felix and Braun, Carsten and Bil, Cees}, title = {Impact of electric propulsion technology and mission requirements on the performance of VTOL UAVs}, series = {CEAS Aeronautical Journal}, volume = {10}, journal = {CEAS Aeronautical Journal}, number = {3}, publisher = {Springer}, issn = {1869-5582 print}, doi = {10.1007/s13272-018-0352-x}, pages = {843}, year = {2018}, abstract = {One of the engineering challenges in aviation is the design of transitioning vertical take-off and landing (VTOL) aircraft. Thrust-borne flight implies a higher mass fraction of the propulsion system, as well as much increased energy consumption in the take-off and landing phases. This mass increase is typically higher for aircraft with a separate lift propulsion system than for aircraft that use the cruise propulsion system to support a dedicated lift system. However, for a cost-benefit trade study, it is necessary to quantify the impact the VTOL requirement and propulsion configuration has on aircraft mass and size. For this reason, sizing studies are conducted. This paper explores the impact of considering a supplemental electric propulsion system for achieving hovering flight. Key variables in this study, apart from the lift system configuration, are the rotor disk loading and hover flight time, as well as the electrical systems technology level for both batteries and motors. Payload and endurance are typically used as the measures of merit for unmanned aircraft that carry electro-optical sensors, and therefore the analysis focuses on these particular parameters.}, language = {en} } @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} } @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 = {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{DachwaldWurm2011, author = {Dachwald, Bernd and Wurm, Patrick}, title = {Mission analysis and performance comparison for an Advanced Solar Photon Thruster}, series = {Advances in Space Research}, volume = {48}, journal = {Advances in Space Research}, number = {11}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0273-1177}, pages = {1858 -- 1868}, year = {2011}, language = {en} } @article{ScholzLeyDachwaldetal.2010, author = {Scholz, A. and Ley, Wilfried and Dachwald, Bernd and Miau, J. J. and Juang, J. C.}, title = {Flight results of the COMPASS-1 picosatellite mission}, series = {Acta Astronautica. 67 (2010), H. 9-10}, journal = {Acta Astronautica. 67 (2010), H. 9-10}, isbn = {0094-5765}, pages = {1289 -- 1298}, year = {2010}, language = {en} } @article{MaiwaldDachwald2010, author = {Maiwald, Volker and Dachwald, Bernd}, title = {Mission Design for a Multiple-Rendezvous Mission to Jupiter's Trojans}, pages = {3}, year = {2010}, language = {en} } @article{FingerGoettenBraunetal.2020, author = {Finger, Felix and G{\"o}tten, Falk and Braun, Carsten and Bil, Cees}, title = {Mass, primary energy, and cost: the impact of optimization objectives on the initial sizing of hybrid-electric general aviation aircraft}, series = {CEAS Aeronautical Journal}, volume = {2020}, journal = {CEAS Aeronautical Journal}, number = {11}, publisher = {Springer}, address = {Heidelberg}, issn = {1869-5590}, doi = {10.1007/s13272-020-00449-8}, pages = {713 -- 730}, year = {2020}, abstract = {For short take-off and landing (STOL) aircraft, a parallel hybrid-electric propulsion system potentially offers superior performance compared to a conventional propulsion system, because the short-take-off power requirement is much higher than the cruise power requirement. This power-matching problem can be solved with a balanced hybrid propulsion system. However, there is a trade-off between wing loading, power loading, the level of hybridization, as well as range and take-off distance. An optimization method can vary design variables in such a way that a minimum of a particular objective is attained. In this paper, a comparison between the optimization results for minimum mass, minimum consumed primary energy, and minimum cost is conducted. A new initial sizing algorithm for general aviation aircraft with hybrid-electric propulsion systems is applied. This initial sizing methodology covers point performance, mission performance analysis, the weight estimation process, and cost estimation. The methodology is applied to the design of a STOL general aviation aircraft, intended for on-demand air mobility operations. The aircraft is sized to carry eight passengers over a distance of 500 km, while able to take off and land from short airstrips. Results indicate that parallel hybrid-electric propulsion systems must be considered for future STOL aircraft.}, language = {en} } @article{FingerBraunBil2020, author = {Finger, Felix and Braun, Carsten and Bil, Cees}, title = {Impact of Battery Performance on the Initial Sizing of Hybrid-Electric General Aviation Aircraft}, series = {Journal of Aerospace Engineering}, volume = {33}, journal = {Journal of Aerospace Engineering}, number = {3}, publisher = {ASCE}, address = {Reston, Va.}, issn = {1943-5525}, doi = {10.1061/(ASCE)AS.1943-5525.0001113}, year = {2020}, abstract = {Studies suggest that hybrid-electric aircraft have the potential to generate fewer emissions and be inherently quieter when compared to conventional aircraft. By operating combustion engines together with an electric propulsion system, synergistic benefits can be obtained. However, the performance of hybrid-electric aircraft is still constrained by a battery's energy density and discharge rate. In this paper, the influence of battery performance on the gross mass for a four-seat general aviation aircraft with a hybrid-electric propulsion system is analyzed. For this design study, a high-level approach is chosen, using an innovative initial sizing methodology to determine the minimum required aircraft mass for a specific set of requirements and constraints. Only the peak-load shaving operational strategy is analyzed. Both parallel- and serial-hybrid propulsion configurations are considered for two different missions. The specific energy of the battery pack is varied from 200 to 1,000 W⋅h/kg, while the discharge time, and thus the normalized discharge rating (C-rating), is varied between 30 min (2C discharge rate) and 2 min (30C discharge rate). With the peak-load shaving operating strategy, it is desirable for hybrid-electric aircraft to use a light, low capacity battery system to boost performance. For this case, the battery's specific power rating proved to be of much higher importance than for full electric designs, which have high capacity batteries. Discharge ratings of 20C allow a significant take-off mass reduction aircraft. The design point moves to higher wing loadings and higher levels of hybridization if batteries with advanced technology are used.}, language = {en} } @article{DachwaldTsinas1994, author = {Dachwald, Bernd and Tsinas, L.}, title = {A combined neural and genetic learning algorithm / Tsinas, L. ; Dachwald, B.}, series = {Proceedings of the First IEEE Conference on Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence.}, journal = {Proceedings of the First IEEE Conference on Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence.}, address = {Orlando, Fl}, isbn = {0-7803-1899-4}, pages = {770 -- 774}, year = {1994}, language = {en} } @article{SchopenShahEschetal.2024, author = {Schopen, Oliver and Shah, Neel and Esch, Thomas and Shabani, Bahman}, title = {Critical quantitative evaluation of integrated health management methods for fuel cell applications}, series = {International Journal of Hydrogen Energy}, volume = {70}, journal = {International Journal of Hydrogen Energy}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0360-3199}, doi = {10.1016/j.ijhydene.2024.05.156}, pages = {370 -- 388}, year = {2024}, abstract = {Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system.}, language = {en} } @article{StiemerThomaBraun2023, author = {Stiemer, Luc Nicolas and Thoma, Andreas and Braun, Carsten}, title = {MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation}, series = {PLoS ONE}, volume = {18}, journal = {PLoS ONE}, number = {9}, publisher = {PLOS}, address = {San Fancisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0291415}, pages = {e0291415}, year = {2023}, abstract = {This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking algorithm for bumblebee tracking. It incorporates an offline trained appearance descriptor along with a Kalman Filter for appearance and motion matching. Different detector architectures for upstream detections (You Only Look Once (YOLOv5), Faster Region Proposal Convolutional Neural Network (Faster R-CNN), and RetinaNet) are investigated in a comparative study to optimize performance. The detection models were trained on a dataset containing 11359 labeled bumblebee images. YOLOv5 reaches an Average Precision of AP = 53, 8\%, Faster R-CNN achieves AP = 45, 3\% and RetinaNet AP = 38, 4\% on the bumblebee validation dataset, which consists of 1323 labeled bumblebee images. The tracker's appearance model is trained on 144 samples. The tracker (with Faster R-CNN detections) reaches a Multiple Object Tracking Accuracy MOTA = 93, 5\% and a Multiple Object Tracking Precision MOTP = 75, 6\% on a validation dataset containing 2000 images, competing with state-of-the-art computer vision methods. The framework allows reliable tracking of different bumblebees in the same video stream with rarely occurring identity switches (IDS). MBT3D has much lower IDS than other commonly used algorithms, with one of the lowest false positive rates, competing with state-of-the-art animal tracking algorithms. The developed framework reconstructs the 3-dimensional (3D) flight paths of the bumblebees by triangulation. It also handles and compares two alternative stereo camera pairs if desired.}, language = {en} } @article{BaaderBoxbergChenetal.2023, author = {Baader, Fabian and Boxberg, Marc S. and Chen, Qian and F{\"o}rstner, Roger and Kowalski, Julia and Dachwald, Bernd}, title = {Field-test performance of an ice-melting probe in a terrestrial analogue environment}, series = {Icarus}, journal = {Icarus}, number = {409}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.1016/j.icarus.2023.115852}, pages = {Artikel 115852}, year = {2023}, abstract = {Melting probes are a proven tool for the exploration of thick ice layers and clean sampling of subglacial water on Earth. Their compact size and ease of operation also make them a key technology for the future exploration of icy moons in our Solar System, most prominently Europa and Enceladus. For both mission planning and hardware engineering, metrics such as efficiency and expected performance in terms of achievable speed, power requirements, and necessary heating power have to be known. Theoretical studies aim at describing thermal losses on the one hand, while laboratory experiments and field tests allow an empirical investigation of the true performance on the other hand. To investigate the practical value of a performance model for the operational performance in extraterrestrial environments, we first contrast measured data from terrestrial field tests on temperate and polythermal glaciers with results from basic heat loss models and a melt trajectory model. For this purpose, we propose conventions for the determination of two different efficiencies that can be applied to both measured data and models. One definition of efficiency is related to the melting head only, while the other definition considers the melting probe as a whole. We also present methods to combine several sources of heat loss for probes with a circular cross-section, and to translate the geometry of probes with a non-circular cross-section to analyse them in the same way. The models were selected in a way that minimizes the need to make assumptions about unknown parameters of the probe or the ice environment. The results indicate that currently used models do not yet reliably reproduce the performance of a probe under realistic conditions. Melting velocities and efficiencies are constantly overestimated by 15 to 50 \% in the models, but qualitatively agree with the field test data. Hence, losses are observed, that are not yet covered and quantified by the available loss models. We find that the deviation increases with decreasing ice temperature. We suspect that this mismatch is mainly due to the too restrictive idealization of the probe model and the fact that the probe was not operated in an efficiency-optimized manner during the field tests. With respect to space mission engineering, we find that performance and efficiency models must be used with caution in unknown ice environments, as various ice parameters have a significant effect on the melting process. Some of these are difficult to estimate from afar.}, language = {en} }