TY - CHAP A1 - Merkens, Torsten A1 - Hebel, Christoph T1 - Sharing mobility concepts – flexible, sustainable, smart T2 - Proceedings of the 1st UNITED – Southeast Asia Automotive Interest Group (SAIG) International Conference KW - Sharing mobility KW - electro mobility KW - business models KW - mobility behaviour Y1 - 2021 SN - 978-3-902103-94-9 N1 - 1st UNITED-SAIG International Conference, 21-22 APR 2021, Chulalongkorn University, Thailand SP - 43 EP - 44 ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Braun, Carsten T1 - Improving the px4 avoid algorithm by bio-inspired flight strategies T2 - DLRK2020 - „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ Y1 - 2020 U6 - https://doi.org/10.25967/530183 N1 - Deutscher Luft- und Raumfahrtkongress 2020, 1. bis 3. September 2020 – Online, „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Bertrand, Olivier A1 - Braun, Carsten ED - Vouloutsi, Vasiliki ED - Mura, Anna ED - Tauber, Falk ED - Speck, Thomas ED - Prescott, Tony J. ED - Verschure, Paul F. M. J. T1 - Evaluation of possible flight strategies for close object evasion from bumblebee experiments T2 - Living Machines 2020: Biomimetic and Biohybrid Systems KW - Obstacle avoidance KW - Bumblebees KW - Flight control KW - UAV KW - MAV Y1 - 2020 SN - 978-3-030-64312-6 U6 - https://doi.org/10.1007/978-3-030-64313-3_34 N1 - 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings SP - 354 EP - 365 PB - Springer CY - Cham ER - 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 - https://doi.org/10.2514/1.C036032 SN - 1533-3868 SP - 1 EP - 13 PB - AIAA CY - Reston, Va. ER - TY - CHAP A1 - Götten, Falk A1 - Finger, Felix A1 - Braun, Carsten A1 - Havermann, Marc A1 - Bil, C. A1 - Gomez, F. T1 - Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles T2 - APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018) N2 - The results of a statistical investigation of 42 fixed-wing, small to medium sized (20 kg−1000 kg) reconnaissance unmanned air vehicles (UAVs) are presented. Regression analyses are used to identify correlations of the most relevant geometry dimensions with the UAV’s maximum take-off mass. The findings allow an empirical based geometry-build up for a complete unmanned aircraft by referring to its take-off mass only. This provides a bridge between very early design stages (initial sizing) and the later determination of shapes and dimensions. The correlations might be integrated into a UAV sizing environment and allow designers to implement more sophisticated drag and weight estimation methods in this process. Additional information on correlation factors for a rough drag estimation methodology indicate how this technique can significantly enhance the accuracy of early design iterations. KW - Unmanned Air Vehicle KW - Geometry KW - Correlations KW - Statistics KW - Drag Y1 - 2019 SN - 978-981-13-3305-7 U6 - https://doi.org/10.1007/978-981-13-3305-7_109 N1 - APISAT 2018 - Asia-Pacific International Symposium on Aerospace Technology. 16-18 October 2018. Chengdu, China. Lecture Notes in Electrical Engineering (LNEE, volume 459) SP - 1365 EP - 1381 PB - Springer CY - Singapore ER - TY - CHAP A1 - Finger, Felix A1 - Götten, Falk A1 - Braun, Carsten A1 - Bil, C. T1 - On Aircraft Design Under the Consideration of Hybrid-Electric Propulsion Systems T2 - APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018) N2 - A hybrid-electric propulsion system combines the advantages of fuel-based systems and battery powered systems and offers new design freedom. To take full advantage of this technology, aircraft designers must be aware of its key differences, compared to conventional, carbon-fuel based, propulsion systems. This paper gives an overview of the challenges and potential benefits associated with the design of aircraft that use hybrid-electric propulsion systems. It offers an introduction of the most popular hybrid-electric propulsion architectures and critically assess them against the conventional and fully electric propulsion configurations. The effects on operational aspects and design aspects are covered. Special consideration is given to the application of hybrid-electric propulsion technology to both unmanned and vertical take-off and landing aircraft. The authors conclude that electric propulsion technology has the potential to revolutionize aircraft design. However, new and innovative methods must be researched, to realize the full benefit of the technology. KW - Hybrid-electric aircraft KW - Aircraft design KW - Design rules KW - Green aircraft Y1 - 2019 SN - 978-981-13-3305-7 U6 - https://doi.org/10.1007/978-981-13-3305-7_99 N1 - APISAT 2018 - Asia-Pacific International Symposium on Aerospace Technology. 16-18 October 2018. Chengdu, China. Lecture Notes in Electrical Engineering (LNEE, volume 459) SP - 1261 EP - 1272 PB - Springer CY - Singapore ER - TY - JOUR A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles JF - SAE International Journal of Commercial Vehicles N2 - The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed. Y1 - 2020 U6 - https://doi.org/10.4271/02-13-02-0009 SN - 1946-3928 VL - 13 IS - 2 SP - 129 EP - 143 PB - SAE International CY - Warrendale, Pa. ER - TY - JOUR A1 - Serror, Martin A1 - Hack, Sacha A1 - Henze, Martin A1 - Schuba, Marko A1 - Wehrle, Klaus T1 - Challenges and Opportunities in Securing the Industrial Internet of Things JF - IEEE Transactions on Industrial Informatics Y1 - 2021 U6 - https://doi.org/10.1109/TII.2020.3023507 SN - 1941-0050 VL - 17 IS - 5 SP - 2985 EP - 2996 PB - IEEE CY - New York ER - TY - JOUR A1 - Hoeveler, B. A1 - Bauknecht, André A1 - Wolf, C. Christian A1 - Janser, Frank T1 - Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight JF - Journal of Aircraft N2 - It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility Göttingen of DLR, German Aerospace Center in Göttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan. Y1 - 2020 U6 - https://doi.org/10.2514/1.C035422 SN - 1533-3868 VL - 57 IS - 4 PB - AIAA CY - Reston, Va. ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 SN - 2169-3536 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Dinghofer, Kai A1 - Hartung, Frank T1 - Analysis of Criteria for the Selection of Machine Learning Frameworks T2 - 2020 International Conference on Computing, Networking and Communications (ICNC) N2 - With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs. Y1 - 2020 U6 - https://doi.org/10.1109/ICNC47757.2020.9049650 N1 - 2020 International Conference on Computing, Networking and Communications (ICNC), 17-20 February 2020, Big Island, HI, USA SP - 373 EP - 377 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Finger, Felix A1 - de Vries, Reynard A1 - Vos, Roelof A1 - Braun, Carsten A1 - Bil, Cees T1 - A comparison of hybrid-electric aircraft sizing methods T2 - AIAA Scitech 2020 Forum N2 - The number of case studies focusing on hybrid-electric aircraft is steadily increasing, since these configurations are thought to lead to lower operating costs and environmental impact than traditional aircraft. However, due to the lack of reference data of actual hybrid-electric aircraft, in most cases, the design tools and results are difficult to validate. In this paper, two independently developed approaches for hybrid-electric conceptual aircraft design are compared. An existing 19-seat commuter aircraft is selected as the conventional baseline, and both design tools are used to size that aircraft. The aircraft is then re-sized under consideration of hybrid-electric propulsion technology. This is performed for parallel, serial, and fully-electric powertrain architectures. Finally, sensitivity studies are conducted to assess the validity of the basic assumptions and approaches regarding the design of hybrid-electric aircraft. Both methods are found to predict the maximum take-off mass (MTOM) of the reference aircraft with less than 4% error. The MTOM and payload-range energy efficiency of various (hybrid-) electric configurations are predicted with a maximum difference of approximately 2% and 5%, respectively. The results of this study confirm a correct formulation and implementation of the two design methods, and the data obtained can be used by researchers to benchmark and validate their design tools. Y1 - 2020 U6 - https://doi.org/10.2514/6.2020-1006 N1 - AIAA Scitech 2020 Forum, Driving aerospace solutions for global challenges, Orlando, 06. - 10. January 2020 ER - TY - CHAP A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude N2 - In addition to very high safety and reliability requirements, the design of internal combustion engines (ICE) in aviation focuses on economic efficiency. The objective must be to design the aircraft powertrain optimized for a specific flight mission with respect to fuel consumption and specific engine power. Against this background, expert tools provide valuable decision-making assistance for the customer. In this paper, a mathematical calculation model for the fuel consumption of aircraft ICE is presented. This model enables the derivation of fuel consumption maps for different engine configurations. Depending on the flight conditions and based on these maps, the current and the integrated fuel consumption for freely definable flight emissions is calculated. For that purpose, an interpolation method is used, that has been optimized for accuracy and calculation time. The mission boundary conditions flight altitude and power requirement of the ICE form the basis for this calculation. The mathematical fuel consumption model is embedded in a parent program. This parent program presents the simulated fuel consumption by means of an example flight mission for a representative airplane. The focus of the work is therefore on reproducing exact consumption data for flight operations. By use of the empirical approaches according to Gagg-Farrar [1] the power and fuel consumption as a function of the flight altitude are determined. To substantiate this approaches, a 1-D ICE model based on the multi-physical simulation tool GT-Suite® has been created. This 1-D engine model offers the possibility to analyze the filling and gas change processes, the internal combustion as well as heat and friction losses for an ICE under altitude environmental conditions. Performance measurements on a dynamometer at sea level for a naturally aspirated ICE with a displacement of 1211 ccm used in an aviation aircraft has been done to validate the 1-D ICE model. To check the plausibility of the empirical approaches with respect to the fuel consumption and performance adjustment for the flight altitude an analysis of the ICE efficiency chain of the 1-D engine model is done. In addition, a comparison of literature and manufacturer data with the simulation results is presented. Y1 - 2020 U6 - https://doi.org/10.25967/490162 N1 - 68. Deutscher Luft- und Raumfahrtkongress 30.09.-02.10.2019, Darmstadt PB - DGLR CY - Bonn ER - TY - JOUR A1 - Rupp, Matthias A1 - Schulze, Sven A1 - Kuperjans, Isabel T1 - Comparative life cycle analysis of conventional and hybrid heavy-duty trucks JF - World electric vehicle journal N2 - Heavy-duty trucks are one of the main contributors to greenhouse gas emissions in German traffic. Drivetrain electrification is an option to reduce tailpipe emissions by increasing energy conversion efficiency. To evaluate the vehicle’s environmental impacts, it is necessary to consider the entire life cycle. In addition to the daily use, it is also necessary to include the impact of production and disposal. This study presents the comparative life cycle analysis of a parallel hybrid and a conventional heavy-duty truck in long-haul operation. Assuming a uniform vehicle glider, only the differing parts of both drivetrains are taken into account to calculate the environmental burdens of the production. The use phase is modeled by a backward simulation in MATLAB/Simulink considering a characteristic driving cycle. A break-even analysis is conducted to show at what mileage the larger CO2eq emissions due to the production of the electric drivetrain are compensated. The effect of parameter variation on the break-even mileage is investigated by a sensitivity analysis. The results of this analysis show the difference in CO2eq/t km is negative, indicating that the hybrid vehicle releases 4.34 g CO2eq/t km over a lifetime fewer emissions compared to the diesel truck. The break-even analysis also emphasizes the advantages of the electrified drivetrain, compensating the larger emissions generated during production after already a distance of 15,800 km (approx. 1.5 months of operation time). The intersection coordinates, distance, and CO2eq, strongly depend on fuel, emissions for battery production and the driving profile, which lead to nearly all parameter variations showing an increase in break-even distance. Y1 - 2018 U6 - https://doi.org/10.3390/wevj9020033 SN - 2032-6653 VL - 9 IS - 2 SP - Article No. 33 PB - MDPI CY - Basel ER - TY - CHAP A1 - Schulze, Sven A1 - Mühleisen, M. A1 - Feyerl, Günter T1 - Adaptive energy management strategy for a heavy-duty truck with a P2-hybrid topology T2 - 18. Internationales Stuttgarter Symposium. Proceedings Y1 - 2018 U6 - https://doi.org/10.1007/978-3-658-21194-3 SP - 75 EP - 89 PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Nowack, N. A1 - Röth, Thilo A1 - Bührig-Polaczek, A. A1 - Klaus, G. ED - Hirsch, Jürgen T1 - Advanced Sheet Metal Components Reinforced by Light Metal Cast Structures T2 - Aluminium alloys : their physical and mechanical properties ; [proceedings of the 11th International Conference on Aluminium Alloys, 22 - 26 Sept. 2008, Aachen, Germany ; ICAA 11] Y1 - 2008 SN - 978-3-527-32367-8 IS - 2 SP - 2374 EP - 2381 ER - TY - CHAP A1 - Neu, Eugen A1 - Janser, Frank A1 - Khatibi, Akbar A. A1 - Orifici, Adrian C. T1 - In-flight vibration-based structural health monitoring of aircraft wings T2 - 30th Congress of the internatonal council of the aeronautical sciences : 25.-30. September 2016, Daejeon, Korea N2 - This work presents a methodology for automated damage-sensitive feature extraction and anomaly detection under multivariate operational variability for in-flight assessment of wings. The method uses a passive excitation approach, i. e. without the need for artificial actuation. The modal system properties (natural frequencies and damping ratios) are used as damage-sensitive features. Special emphasis is placed on the use of Fiber Bragg Grating (FBG) sensing technology and the consideration of Operational and Environmental Variability (OEV). Measurements from a wind tunnel investigation with a composite cantilever equipped with FBG and piezoelectric sensors are used to successfully detect an impact damage. In addition, the feasibility of damage localisation and severity estimation is evaluated based on the coupling found between damageand OEV-induced feature changes. Y1 - 2016 ER - TY - CHAP A1 - Wu, Ziyi A1 - Kemper, Hans T1 - The optimal 48 V – battery pack for a specific load profile of a heavy duty vehicle T2 - 8. Internationale Fachtagung Kraftwerk Batterie : 26. – 27. April 2016, Münster, Deutschland Y1 - 2016 ER - TY - JOUR A1 - Neu, Eugen A1 - Janser, Frank A1 - Khatibi, Akbar A. A1 - Orifici, Adrian C. T1 - Fully Automated Operational Modal Analysis using multi-stage clustering JF - Mechanical Systems and Signal Processing Y1 - 2017 U6 - https://doi.org/10.1016/j.ymssp.2016.07.031 SN - 0888-3270 VL - Vol. 84, Part A SP - 308 EP - 323 PB - Elsevier CY - Amsterdam ER -