TU Darmstadt / ULB / TUbiblio

Browse by Person

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: No Grouping | Item Type | Date | Language
Number of items: 12.

Blat Belmonte, Benjamin and Eßer, Arved and Weyand, Steffi and Franke, Georg and Schebek, Liselotte and Rinderknecht, Stephan (2020):
Identification of the Optimal Passenger Car Vehicle Fleet Transition for Mitigating the Cumulative Life-Cycle Greenhouse Gas Emissions until 2050.
In: Vehicles: Special Issue "Future Powertrain Technologies", 2 (1), 2020. MDPI, pp. 75-99, e-ISSN 2624-8921,
[Online-Edition: https://www.mdpi.com/2624-8921/2/1/5],
[Article]

Eßer, Arved and Schleiffer, J.-E. and Eichenlaub, Tobias and Rinderknecht, Stephan (2020):
Development of an Optimization Framework for the Comparative Evaluation of the Ecoimpact of Powertrain Concepts.
2354In: VDI-Berichte, Bonn, 10.-11. Juli 2019, In: 19. Internationaler VDI-Kongress "Dritev - Getriebe in Fahrzeugen", ISBN 978-3-18-092354-3,
DOI: 10.25534/tuprints-00011299,
[Online-Edition: https://tuprints.ulb.tu-darmstadt.de/11299],
[Conference or Workshop Item]

Rinderknecht, Stephan and Viehmann, Andreas and Eßer, Arved and Langhammer, Felix (2019):
Dedizierte Hybridantriebe für eine ökoeffiziente und langstreckentaugliche Mobilität der Zukunft.
In: eMobilJournal, (Juli 2019), InnoTech Medien GmbH, ISSN 2568-213X,
[Online-Edition: https://www.emobilserver.de/emobil-exklusiv/1818-dedizierte-...],
[Article]

Jardin, Philippe and Eßer, Arved and Givone, S. and Eichenlaub, Tobias and Schleiffer, J.-E. and Rinderknecht, Stephan (2019):
The Sensitivity in Consumption of Different Vehicle Drivetrain Concepts Under Varying Operating Conditions: A Simulative Data Driven Approach.
In: Vehicles — Open Access Journal from MDPI, [Online-Edition: https://www.mdpi.com/journal/vehicles],
[Article]

Rinderknecht, Stephan and Eßer, Arved and Haccius, Jan P. (2018):
Ecologically effective transformation from fossil to CO2-neutral energy sources for the powertrains of individual mobility.
In: 17th CTI SYMPOSIUM, Berlin, Dezember 2018, [Conference or Workshop Item]

Eßer, Arved and Kohnhäuser, F. and Ostern, N. and Engleson, K. and Rinderknecht, Stephan (2018):
Enabling a Privacy-Preserving Synthesis of Representative Driving Cycles from Fleet Data using Data Aggregation.
In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 1384-1389, [Online-Edition: https://ieeexplore.ieee.org/document/8569429],
[Article]

Rinderknecht, Stephan and Eßer, Arved and Schleiffer, J.-E. and Eichenlaub, Tobias (2018):
Comparative Real-Driving Optimization of Drivetrain Concepts regarding the Ecological Impact - A Big Data Approach for the Fleet.
In: eDSIM Conference 2018 - Electrified Drivelines & Engineering 4.0, Darmstadt, Deutschland, [Conference or Workshop Item]

Rinderknecht, Stephan and Viehmann, Andreas and Eßer, Arved (2018):
Innovative elektrifizierte Fahrzeugantriebe im Kontext der Realfahrtoptimierung.
In: Ingenieurspiegel, (August 2018), Public Verlagsgesellschaft, Bingen, pp. 35-37, [Article]

Rinderknecht, Stephan and Eßer, Arved and Jardin, Philippe (2018):
Relevance of Multidimensional Real-Driving Optimization for the Development of a Battery-Electric Vehicle 5.0.
In: VDI-Berichte, In: Dritev - International VDI Conress EDrive, VDI Verlag, pp. 118-136, [Book Section]

Eßer, Arved and Zeller, M. and Foulard, Stéphane and Rinderknecht, Stephan (2018):
Stochastic Synthesis of Representative and Multidimensional Driving Cycles.
In: SAE International Journal of Alternative Powertrains, 7 (3), pp. 263-272, ISSN 2167-4205,
[Online-Edition: https://doi.org/10.4271/2018-01-0095],
[Article]

Ostern (geborene Rückeshäuser), Nadine and Eßer, Arved and Buxmann, Peter (2018):
Capturing Users‘ Privacy Expectations to Design Better Smart Car Applications.
In: Proceedings of the 22nd Pacific Asia Conference on Information Systems, Yokohama, Japan, [Article]

Eßer, Arved and Kohnhäuser, Florian and Ostern (geborene Rückeshäuser), Nadine and Engleson, K. and Rinderknecht, Stephan (2018):
Enabling a Privacy-Preserving Synthesis of Representative Driving Cycles from Fleet Data using Data Aggregation.
In: Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, [Article]

This list was generated on Tue May 26 00:16:33 2020 CEST.