@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}
}
@article{UlmerBraunChengetal.2023,
  author    = {Ulmer, Jessica and Braun, Carsten and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation},
  series = {International Journal of Production Research},
  journal   = {International Journal of Production Research},
  publisher = {Taylor \& Francis},
  issn      = {0020-7543 (Print)},
  doi       = {10.1080/00207543.2023.2166140},
  year      = {2023},
  abstract  = {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.},
  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}
}
@article{PfaffEnningSutter2022,
  author    = {Pfaff, Raphael and Enning, Manfred and Sutter, Stefan},
  title     = {A risk‑based approach to automatic brake tests for rail freight service: incident analysis and realisation concept},
  series = {SN Applied Sciences},
  volume    = {4},
  journal   = {SN Applied Sciences},
  number    = {4},
  publisher = {Springer},
  address   = {Cham},
  issn      = {2523-3971},
  doi       = {10.1007/s42452-022-05007-x},
  pages     = {1 -- 14},
  year      = {2022},
  abstract  = {This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual labour and increased productivity.},
  language  = {en}
}
@article{BoehnischBraunMuscarelloetal.2023,
  author    = {B{\"o}hnisch, Nils and Braun, Carsten and Muscarello, Vincenzo and Marzocca, Pier},
  title     = {A sensitivity study on aeroelastic instabilities of slender wings with a large propeller},
  series = {AIAA SCITECH 2023 Forum},
  journal   = {AIAA SCITECH 2023 Forum},
  publisher = {AIAA},
  doi       = {10.2514/6.2023-1893},
  pages     = {1 -- 14},
  year      = {2023},
  abstract  = {Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan. These highly flexible dynamic systems can exhibit uncommon aeroelastic instabilities, which should be carefully investigated to ensure safe operation. The interaction between the propeller and the wing is of particular importance. It is known that whirl flutter is stabilized by wing motion and wing aerodynamics. This paper investigates the effect of a propeller onto wing flutter as a function of span position and mounting stiffness between the propeller and wing. The analysis of a comparison between a tractor and pusher configuration has shown that the coupled system is more stable than the standalone wing for propeller positions near the wing tip for both configurations. The wing fluttermechanism is mostly affected by the mass of the propeller and the resulting change in eigenfrequencies of the wing. For very weak mounting stiffnesses, whirl flutter occurs, which was shown to be stabilized compared to a standalone propeller due to wing motion. On the other hand, the pusher configuration is, as to be expected, the more critical configuration due to the attached mass behind the elastic axis.},
  language  = {de}
}
@article{BoehnischBraunMuscarelloetal.2024,
  author    = {B{\"o}hnisch, Nils and Braun, Carsten and Muscarello, Vincenzo and Marzocca, Pier},
  title     = {About the wing and whirl flutter of a slender wing-propeller system},
  series = {Journal of Aircraft},
  journal   = {Journal of Aircraft},
  publisher = {American Institute of Aeronautics and Astronautics},
  issn      = {1533-3868},
  doi       = {10.2514/1.C037542},
  pages     = {1 -- 14},
  year      = {2024},
  abstract  = {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.},
  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{SchwagerFleschSchwarzboezletal.2022,
  author    = {Schwager, Christian and Flesch, Robert and Schwarzb{\"o}zl, Peter and Herrmann, Ulf and Teixeira Boura, Cristiano Jos{\´e}},
  title     = {Advanced two phase flow model for transient molten salt receiver system simulation},
  series = {Solar Energy},
  volume    = {232},
  journal   = {Solar Energy},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0038-092X (print)},
  doi       = {10.1016/j.solener.2021.12.065},
  pages     = {362 -- 375},
  year      = {2022},
  abstract  = {In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.},
  language  = {en}
}
@article{WeiheErnstRoethetal.2013,
  author    = {Weihe, Stefan and Ernst, Ansgar and R{\"o}th, Thilo and Proksch, Johannes},
  title     = {Aluminium-Stahl-Verbundguss im Nutzfahrzeugbau},
  series = {ATZ - Automobiltechnische Zeitschrift},
  volume    = {115},
  journal   = {ATZ - Automobiltechnische Zeitschrift},
  number    = {4},
  publisher = {Springer Fachmedien Wiesbaden},
  issn      = {2192-8800 (Online)},
  pages     = {312 -- 316},
  year      = {2013},
  abstract  = {In modernen Fahrzeugkarosserien der Großserie kommen zunehmend Materialmischbauweisen zur Anwendung. In Zusammenarbeit der Daimler AG, der Tower Automotive Holding GmbH, der Imperia GmbH sowie der Partnerunternehmen KSM Castings GmbH und Schaufler Tooling GmbH \& Co. KG wird das Leichtbaupotenzial von Aluminiumverbundguss-Stahlblech-Hybriden am Beispiel des vorderen Dachquertr{\"a}gers des Mercedes-Benz Viano/Vito ausf{\"u}hrlich untersucht.},
  language  = {de}
}