@article{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles}, series = {SAE International Journal of Commercial Vehicles}, volume = {13}, journal = {SAE International Journal of Commercial Vehicles}, number = {2}, publisher = {SAE International}, address = {Warrendale, Pa.}, issn = {1946-3928}, doi = {10.4271/02-13-02-0009}, pages = {129 -- 143}, year = {2020}, abstract = {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.}, language = {en} } @inproceedings{FingerdeVriesVosetal.2020, author = {Finger, Felix and de Vries, Reynard and Vos, Roelof and Braun, Carsten and Bil, Cees}, title = {A comparison of hybrid-electric aircraft sizing methods}, series = {AIAA Scitech 2020 Forum}, booktitle = {AIAA Scitech 2020 Forum}, doi = {10.2514/6.2020-1006}, pages = {31 Seiten}, year = {2020}, language = {en} } @inproceedings{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude}, series = {Deutscher Luft- und Raumfahrtkongress 2019, „Luft- und Raumfahrt - technologische Br{\"u}cke in die Zukunft", Darmstadt, 30. September bis 2. Oktober 2019}, booktitle = {Deutscher Luft- und Raumfahrtkongress 2019, „Luft- und Raumfahrt - technologische Br{\"u}cke in die Zukunft", Darmstadt, 30. September bis 2. Oktober 2019}, publisher = {Deutsche Gesellschaft f{\"u}r Luft- und Raumfahrt - Lilienthal-Oberth e.V}, address = {Bonn}, doi = {10.25967/490162}, pages = {13 Seiten}, year = {2020}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, number = {Art. 9108222}, publisher = {IEEE}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {111381 -- 111393}, year = {2020}, abstract = {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.}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0}, series = {IEEE Access}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York, NY}, isbn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {1 -- 12}, year = {2020}, abstract = {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.}, language = {en} } @inproceedings{GeibenGoettenHavermann2020, author = {Geiben, Benedikt and G{\"o}tten, Falk and Havermann, Marc}, title = {Aerodynamic analysis of a winged sub-orbital spaceplane}, series = {Deutscher Luft- und Raumfahrtkongress - DLRK 2020}, booktitle = {Deutscher Luft- und Raumfahrtkongress - DLRK 2020}, year = {2020}, language = {en} } @article{GoettenHavermannBraunetal.2020, author = {G{\"o}tten, Falk and Havermann, Marc and Braun, Carsten and Marino, Matthew and Bil, Cees}, title = {Airfoil drag at low-to-medium reynolds numbers: A novel estimation method}, series = {AIAA Journal}, volume = {58}, journal = {AIAA Journal}, number = {7}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-385X}, doi = {10.2514/1.J058983}, pages = {2791 -- 2805}, year = {2020}, abstract = {This paper presents a novel method for airfoil drag estimation at Reynolds numbers between 4×10⁵ and 4×10⁶. The novel method is based on a systematic study of 40 airfoils applying over 600 numerical simulations and considering natural transition. The influence of the airfoil thickness-to-chord ratio, camber, and freestream Reynolds number on both friction and pressure drag is analyzed in detail. Natural transition significantly affects drag characteristics and leads to distinct drag minima for different Reynolds numbers and thickness-to-chord ratios. The results of the systematic study are used to develop empirical correlations that can accurately predict an airfoil drag at low-lift conditions. The new approach estimates a transition location based on airfoil thickness-to-chord ratio, camber, and Reynolds number. It uses the transition location in a mixed laminar-turbulent skin-friction calculation, and corrects the skin-friction coefficient for separation effects. Pressure drag is estimated separately based on correlations of thickness-to-chord ratio, camber, and Reynolds number. The novel method shows excellent accuracy when compared with wind-tunnel measurements of multiple airfoils. It is easily integrable into existing aircraft design environments and is highly beneficial in the conceptual design stage.}, language = {en} } @article{FingerBraunBil2020, author = {Finger, Felix and Braun, Carsten and Bil, Cees}, title = {Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft}, series = {Journal of Aircraft}, volume = {57}, journal = {Journal of Aircraft}, number = {5}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-3868}, doi = {10.2514/1.C035897}, year = {2020}, abstract = {Until electric energy storage systems are ready to allow fully electric aircraft, the combination of combustion engine and electric motor as a hybrid-electric propulsion system seems to be a promising intermediate solution. Consequently, the design space for future aircraft is expanded considerably, as serial hybrid-electric, parallel hybrid-electric, fully electric, and conventional propulsion systems must all be considered. While the best propulsion system depends on a multitude of requirements and considerations, trends can be observed for certain types of aircraft and certain types of missions. This Paper provides insight into some factors that drive a new design toward either conventional or hybrid propulsion systems. General aviation aircraft, regional transport aircraft vertical takeoff and landing air taxis, and unmanned aerial vehicles are chosen as case studies. Typical missions for each class are considered, and the aircraft are analyzed regarding their takeoff mass and primary energy consumption. For these case studies, a high-level approach is chosen, using an initial sizing methodology. Only parallel-hybrid-electric powertrains are taken into account. Aeropropulsive interaction effects are neglected. Results indicate that hybrid-electric propulsion systems should be considered if the propulsion system is sized by short-duration power constraints. However, if the propulsion system is sized by a continuous power requirement, hybrid-electric systems offer hardly any benefit.}, language = {en} } @inproceedings{FingerBraunBil2020, author = {Finger, Felix and Braun, Carsten and Bil, Cees}, title = {Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft}, series = {AIAA SciTech Forum 2020, 06.01.2020 - 10.01.2020, Orlando}, booktitle = {AIAA SciTech Forum 2020, 06.01.2020 - 10.01.2020, Orlando}, doi = {10.2514/6.2020-1502}, pages = {15 Seiten}, year = {2020}, language = {en} } @article{HailerWeberNevelingetal.2020, author = {Hailer, Benjamin and Weber, Tobias and Neveling, Sebastian and Dera, Samuel and Arent, Jan-Christoph and Middendorf, Peter}, title = {Development of a test device to determine the frictional behavior between honeycomb and prepreg layers under realistic manufacturing conditions}, series = {Journal of Sandwich Structures \& Materials}, journal = {Journal of Sandwich Structures \& Materials}, number = {Volume 23, Issue 7}, publisher = {Sage}, address = {London}, issn = {1530-7972}, doi = {10.1177/1099636220923986}, pages = {3017 -- 3043}, year = {2020}, abstract = {In the friction tests between honeycomb with film adhesive and prepreg, the relative displacement occurs between the film adhesive and the prepreg. The film adhesive does not shift relative to the honeycomb. This is consistent with the core crush behavior where the honeycomb moves together with the film adhesive, as can be seen in Figure 2(a). The pull-through forces of the friction measurements between honeycomb and prepreg at 1 mm deformation are plotted in Figure 17(a). While the friction at 100°C is similar to the friction at 120°C, it decreases significantly at 130°C and exhibits a minimum at 140°C. At 150°C, the friction rises again slightly and then sharply at 160°C. Since the viscosity of the M18/1 prepreg resin drops significantly before it cures [23], the minimum friction at 140°C could result from a minimum viscosity of the mixture of prepreg resin and film adhesive before the bond subsequently cures. Figure 17(b) shows the mean value curve of the friction measurements at 140°C. The error bars, which represent the standard deviation, reveal the good repeatability of the tests. The force curve is approximately horizontal between 1 mm and 2 mm. The friction then slightly rises. As with interlaminar friction measurements, this could be due to the fact that resin is removed by friction and the proportion of boundary lubrication increases. Figure 18 shows the surfaces after the friction measurement. The honeycomb cell walls are clearly visible in the film adhesive. There are areas where the film adhesive is completely removed and the carrier material of the film adhesive becomes visible. In addition, the viscosity of the resin changes as the curing progresses during the friction test. This can also affect the force-displacement curve.}, language = {en} }