TY - JOUR A1 - Götten, Falk A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, Matthew A1 - Bil, Cees T1 - Improved Form Factor for Drag Estimation of Fuselages with Various Cross Sections JF - Journal of Aircraft N2 - The paper presents an aerodynamic investigation of 70 different streamlined bodies with fineness ratios ranging from 2 to 10. The bodies are chosen to idealize both unmanned and small manned aircraft fuselages and feature cross-sectional shapes that vary from circular to quadratic. The study focuses on friction and pressure drag in dependency of the individual body’s fineness ratio and cross section. The drag forces are normalized with the respective body’s wetted area to comply with an empirical drag estimation procedure. Although the friction drag coefficient then stays rather constant for all bodies, their pressure drag coefficients decrease with an increase in fineness ratio. Referring the pressure drag coefficient to the bodies’ cross-sectional areas shows a distinct pressure drag minimum at a fineness ratio of about three. The pressure drag of bodies with a quadratic cross section is generally higher than for bodies of revolution. The results are used to derive an improved form factor that can be employed in a classic empirical drag estimation method. The improved formulation takes both the fineness ratio and cross-sectional shape into account. It shows superior accuracy in estimating streamlined body drag when compared with experimental data and other form factor formulations of the literature. Y1 - 2020 U6 - http://dx.doi.org/10.2514/1.C036032 SN - 1533-3868 SP - 1 EP - 13 PB - AIAA CY - Reston, Va. ER - TY - JOUR A1 - Funke, Harald A1 - Esch, Thomas A1 - Roosen, Petra T1 - Powertrain Adaptions for LPG Usage in General Aviation JF - MTZ worldwide N2 - 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. Y1 - 2022 U6 - http://dx.doi.org/10.1007/s38313-021-0756-6 VL - 2022 IS - 83 SP - 58 EP - 62 PB - Springer Nature CY - Basel ER - TY - JOUR A1 - Schulze, Sven A1 - Feyerl, Günter A1 - Pischinger, Stefan T1 - Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions JF - Energies N2 - 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. KW - Energy management strategies KW - ECMS KW - CO2 emission reduction targets KW - Driving cycle recognition KW - Predictive battery discharge Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16135171 SN - 1996-1073 N1 - The article belongs to the Special Issue "Energy Management Strategies of Electrified Vehicles toward the Real-World Driving". VL - 16 IS - 13 PB - MDPI CY - Basel ER - TY - JOUR A1 - Esch, Thomas T1 - Trends in commercial vehicle powertrains JF - ATZautotechnology N2 - 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. KW - European Transient Cycle KW - Common Rail Injection System KW - Commercial Vehicle KW - Selective Catalytic Reduction KW - Diesel Engine Y1 - 2010 U6 - http://dx.doi.org/10.1007/BF03247185 SN - 2192-886X VL - 2010 IS - 10 SP - 26 EP - 31 PB - Vieweg & Sohn CY - Wiesbaden ER - TY - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich T1 - System concept and realization of a scalable neurocomputing architecture JF - Systems Analysis Modelling Simulation N2 - This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies. Y1 - 1999 SN - 0232-9298 SN - 1029-4902 VL - 35 IS - 4 SP - 399 EP - 419 PB - Gordon and Breach Science Publishers CY - Amsterdam ER - TY - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich A1 - Krumbiegel, Dirk A1 - Walter, Peter A1 - Wickel, Jochen T1 - Visual information retrieval for 3D product identification: a midterm report JF - KI - Künstliche Intelligenz Y1 - 1999 SN - 1610-1987 SN - 0933-1875 VL - 13 IS - 1 SP - 64 EP - 67 PB - Springer CY - Berlin ER - TY - JOUR A1 - Elsen, Ingo A1 - Hartung, Frank A1 - Horn, Uwe A1 - Kampmann, Markus A1 - Peters, Liliane ED - Voas, Jeffrey T1 - Streaming technology in 3G mobile communication systems JF - Computer : innovative technology for computer professionals N2 - Third-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality Internet content that meets the specific needs of the rapidly growing mobile market. Y1 - 2001 SN - 0018-9162 SN - 1558-0814 VL - 34 IS - 9 Seiten SP - 46 EP - 52 PB - IEEE CY - New York ER - TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - 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. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - http://dx.doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel ER - TY - JOUR A1 - Thoma, Andreas A1 - Thomessen, Karolin A1 - Gardi, Alessandro A1 - Fisher, A. A1 - Braun, Carsten T1 - Prioritising paths: An improved cost function for local path planning for UAV in medical applications JF - The Aeronautical Journal N2 - Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability. KW - Path planning KW - Cost function KW - Multi-objective optimization Y1 - 2023 U6 - http://dx.doi.org/10.1017/aer.2023.68 SN - 0001-9240 (Print) SN - 2059-6464 (Online) IS - First View SP - 1 EP - 18 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Pfaff, Raphael T1 - Braking distance prediction for vehicle consist in low-speed on-sight operation: a Monte Carlo approach JF - Railway Engineering Science N2 - The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes. KW - Freight rail KW - Shunting KW - Braking curves KW - Brake set-up KW - Driver assistance system Y1 - 2023 U6 - http://dx.doi.org/10.1007/s40534-023-00303-7 SN - 2662-4753 (eISSN) SN - 2662-4745 (Print) VL - 31 IS - 2 SP - 135 EP - 144 PB - SpringerOpen ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Carsten A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation JF - International Journal of Production Research N2 - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines. KW - Human factors KW - assistance system KW - gamification KW - adaptive systems KW - manufacturing Y1 - 2023 U6 - http://dx.doi.org/10.1080/00207543.2023.2166140 SN - 0020-7543 (Print) SN - 1366-588X (Online) PB - Taylor & Francis ER - TY - JOUR A1 - Böhnisch, Nils A1 - Braun, Carsten A1 - Muscarello, Vincenzo A1 - Marzocca, Pier T1 - About the wing and whirl flutter of a slender wing–propeller system JF - Journal of Aircraft N2 - Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan (distributed electric propulsion), leading to highly flexible dynamic systems that can exhibit aeroelastic instabilities. This paper introduces a validated methodology to investigate the aeroelastic instabilities of wing–propeller systems and to understand the dynamic mechanism leading to wing and whirl flutter and transition from one to the other. Factors such as nacelle positions along the wing span and chord and its propulsion system mounting stiffness are considered. Additionally, preliminary design guidelines are proposed for flutter-free wing–propeller systems applicable to novel aircraft designs. The study demonstrates how the critical speed of the wing–propeller systems is influenced by the mounting stiffness and propeller position. Weak mounting stiffnesses result in whirl flutter, while hard mounting stiffnesses lead to wing flutter. For the latter, the position of the propeller along the wing span may change the wing mode shapes and thus the flutter mechanism. Propeller positions closer to the wing tip enhance stability, but pusher configurations are more critical due to the mass distribution behind the elastic axis. Y1 - 2024 U6 - http://dx.doi.org/10.2514/1.C037542 SN - 1533-3868 SP - 1 EP - 14 PB - American Institute of Aeronautics and Astronautics ER - TY - JOUR A1 - Stiemer, Luc Nicolas A1 - Thoma, Andreas A1 - Braun, Carsten T1 - MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation JF - PLoS ONE N2 - 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. Y1 - 2023 U6 - http://dx.doi.org/10.1371/journal.pone.0291415 SN - 1932-6203 N1 - Corresponding author: Luc Nicolas Stiemer VL - 18 IS - 9 PB - PLOS CY - San Fancisco ER -