TY - JOUR A1 - Esch, Thomas A1 - Salber, Wolfgang A1 - Wolters, Peter A1 - Geiger, José A1 - Dilthey, Jochen T1 - Synergies of variable valve actuation and direct injection JF - Direct injection SI engine technology 2002 : [SAE 2002 world congress, Detroit, Michigan, USA, March 4 - 7, 2002]. Y1 - 2002 SN - 0-7680-0961-8 N1 - Konferenz-Einzelbericht SP - 45 EP - 53 PB - Society of Automotive Engineers CY - Warrendale, Pa ER - TY - JOUR A1 - Esch, Thomas T1 - Optimized design of the lubrication system of modern combustion engines. Verbesserte Ausführung von Schmierungssystemen bei modernen Verbrennungsmotoren Y1 - 1991 SN - 0148-7191 U6 - http://dx.doi.org/10.4271/912407 N1 - Konferenz-Einzelbericht : SAE technical papers / Society of Automotive Engineers, Paper-Nr. 912407 SP - 1 EP - 11 ER - TY - JOUR A1 - Esch, Thomas A1 - Funke, Harald A1 - Roosen, Peter A1 - Jarolimek, Ulrich T1 - Biogenic Vehicle Fuels in General Aviation Aircrafts JF - MTZ worldwide. 72 (2011), H. 1 Y1 - 2011 N1 - recherchierbar für Angehörige der FH Aachen SP - 38 EP - 43 PB - Springer Automotive Media CY - Wiesbaden ER - TY - CHAP A1 - Busse, Daniel A1 - Esch, Thomas A1 - Muntaniol, Roman T1 - Thermal management in E-carsharing vehicles - preconditioning concepts of passenger compartments T2 - E-Mobility in Europe : trends and good practice N2 - The issue of thermal management in electric vehicles includes the topics of drivetrain cooling and heating, interior temperature, vehicle body conditioning and safety. In addition to the need to ensure optimal thermal operating conditions of the drivetrain components (drive motor, battery and electrical components), thermal comfort must be provided for the passengers. Thermal comfort is defined as the feeling which expresses the satisfaction of the passengers with the ambient conditions in the compartment. The influencing factors on thermal comfort are the temperature and humidity as well as the speed of the indoor air and the clothing and the activity of the passengers, in addition to the thermal radiation and the temperatures of the interior surfaces. The generation and the maintenance of free visibility (ice- and moisture-free windows) count just as important as on-demand heating and cooling of the entire vehicle. A Carsharing climate concept of the innovative ec2go vehicle stipulates and allows for only seating areas used by passengers to be thermally conditioned in a close-to-body manner. To enable this, a particular feature has been added to the preconditioning of the Carsharing electric vehicle during the electric charging phase at the parking station. KW - Carsharing KW - Thermal management KW - Thermal comfort KW - Electrical vehicle KW - Passenger compartment Y1 - 2015 SN - 978-3-319-13193-1 U6 - http://dx.doi.org/10.1007/978-3-319-13194-8_18 SP - 327 EP - 343 PB - Springer CY - Cham [u.a.] 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 - http://dx.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 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY 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 - http://dx.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 - CHAP A1 - Haugg, Albert Thomas A1 - Kreyer, Jörg A1 - Kemper, Hans A1 - Hatesuer, Katerina A1 - Esch, Thomas T1 - Heat exchanger for ORC. adaptability and optimisation potentials T2 - IIR International Rankine 2020 Conference N2 - The recovery of waste heat requires heat exchangers to extract it from a liquid or gaseous medium into another working medium, a refrigerant. In Organic Rankine Cycles (ORC) on Combustion Engines there are two major heat sources, the exhaust gas and the water/glycol fluid from the engine’s cooling circuit. A heat exchanger design must be adapted to the different requirements and conditions resulting from the heat sources, fluids, system configurations, geometric restrictions, and etcetera. The Stacked Shell Cooler (SSC) is a new and very specific design of a plate heat exchanger, created by AKG, which allows with a maximum degree of freedom the optimization of heat exchange rate and the reduction of the related pressure drop. This optimization in heat exchanger design for ORC systems is even more important, because it reduces the energy consumption of the system and therefore maximizes the increase in overall efficiency of the engine. Y1 - 2020 U6 - http://dx.doi.org/10.18462/iir.rankine.2020.1224 N1 - Conference: IIR International Rankine 2020 Conference - Heating, Cooling, Power Generation. Glasgow, 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 T2 - Deutscher Luft- und Raumfahrtkongress 2019, „Luft- und Raumfahrt – technologische Brücke in die Zukunft“, Darmstadt, 30. September bis 2. Oktober 2019 Y1 - 2020 U6 - http://dx.doi.org/10.25967/490162 PB - Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V CY - Bonn ER - TY - CHAP A1 - Finger, Felix A1 - Khalsa, R. A1 - Kreyer, Jörg A1 - Mayntz, Joscha A1 - Braun, Carsten A1 - Dahmann, Peter A1 - Esch, Thomas A1 - Kemper, Hans A1 - Schmitz, O. A1 - Bragard, Michael T1 - An approach to propulsion system modelling for the conceptual design of hybrid-electric general aviation aircraft T2 - Deutscher Luft- und Raumfahrtkongress 2019, 30.9.-2.10.2019, Darmstadt N2 - In this paper, an approach to propulsion system modelling for hybrid-electric general aviation aircraft is presented. Because the focus is on general aviation aircraft, only combinations of electric motors and reciprocating combustion engines are explored. Gas turbine hybrids will not be considered. The level of the component's models is appropriate for the conceptual design stage. They are simple and adaptable, so that a wide range of designs with morphologically different propulsive system architectures can be quickly compared. Modelling strategies for both mass and efficiency of each part of the propulsion system (engine, motor, battery and propeller) will be presented. Y1 - 2019 ER -