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Number of items: 9.

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, Public Verlagsgesellschaft, Bingen, pp. 35-37, (August 2018), [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: 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, pp. 263-272, 7, (3), 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 Jun 18 00:39:10 2019 CEST.