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Suche nach „[Diana] [Schramm]“ hat 7 Publikationen gefunden
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    MobilF: Elektrotechnik und Medientechnik

    Zeitschriftenartikel

    Diana Schramm, Nicki Bodenschatz, Andreas Berl

    Usage Profiling in Electric Vehicles

    Bavarian Journal of Applied Sciences, vol. 4, no. 1, pp. 342-353

    2018

    DOI: 10.25929/bjas.v4i1.52

    Abstract anzeigen

    In the overall effort of reducing CO2 emissions, the significance of alternative drive engines is growing. The transition from combustion engine vehicles to electric vehicles is high on the political agendas, with governments providing extensive funding to promote electric mobility. However, there are still challenges that hamper the dissemination of electric vehicles. One of those challenges is the limited range and the resulting range anxiety. Displayed vehicle range data contribute to this, as they are relatively inaccurate and might vary quite strongly during individual trips. This problem could be addressed by personalizing the range display according to the driving style of the current driver. Driver assistance services, like distance control, are becoming increasingly personalized nowadays, however, they are predominantly designed for internal combustion engine vehicles. In this paper, relevant input parameters for classifying the driving styles of electric vehicle users are identified. Furthermore, a system based on real-life driving data is developed to determine the driving style. Real-life driving data were collected in experiments and used to profile the driving style by means of fuzzy logic. Based on the results, an approach for a realistic classification of driving styles of electric vehicle users is discussed.

    MobilS: TC Freyung

    Vortrag

    Nicki Bodenschatz, Markus Eider, Diana Schramm, Andreas Berl

    Optimierte Ladeplanung von Elektrofahrzeugflotten

    Posterpräsentation

    5. Tag der Forschung, Deggendorf

    2018

    MobilS: TC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Nicki Bodenschatz, Diana Schramm, Markus Eider, Andreas Berl

    Classification of Electric Vehicle Fleets Considering the Complexity of Fleet Charging Schedules

    [Status: Presented]

    ACM e-Energy '18: Proceedings of the Ninth ACM International Conference on Future Energy Systems (June 12-15, 2018; Karlsruhe, Germany), New York, NY

    2018

    ISBN: 978-1-4503-5767-8

    DigitalS: TC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Markus Eider, Diana Schramm, Nicki Bodenschatz, Andreas Berl, P. Danner, H. Meer

    A Novel Approach on Battery Health Monitoring

    Proceedings of the 7th Conference on Future Automotive Technology (CoFAT) [May 8th-9th, 2018; Fürstenfeldbruck]

    2018

    MobilS: TC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Markus Eider, Diana Schramm, Andreas Berl, R. Basmadjian, H. Meer, S. Klingert, T. Schulze, F. Kutzner, C. Kacperski, M. Štolba

    Seamless Electromobility

    ACM e-Energy '17: Proceedings of the Eighth ACM International Conference on Future Energy Systems (May 16-19, 2017; Shatin, Hong Kong), New York NY

    2017

    ISBN: 978-1-4503-5036-5

    DOI: 10.1145/3077839.3078461

    Abstract anzeigen

    The existing electromobility (EM) is still in its fledgling stage and multiple challenges have to be overcome to make Electric Vehicles (EVs) as convenient as combustion engine vehicles. Users and Electric Vehicle Fleet Operators (EFOs) want their EVs to be charged and ready for use at all times. This straightforward goal, however, is counteracted from various sides: The range of the EV depends on the status and depletion of the EV battery which is influenced by EV use and charging characteristics. Also, most convenient charging from the user's point of view, might unfortunately lead to problems in the power grid. As in the case of a power peak in the evening when EV users return from work and simultaneously plug in their EVs for charging. Last but not least, the mass of EV batteries are an untapped potential to store electricity from intermittent renewable energy sources. In this paper, we propose a novel approach to tackle this multi-layered problem from different perspectives. Using on-board EV data and grid prediction models, we build up an information model as a foundation for a back end service containing EFO and Charging Station Provider (CSP) logic as well as a central Advanced Drivers Assistant System (ADAS). These components connect to both battery management and user interfaces suggesting various routing and driving behaviour alternatives customized and incentivized for the current user profile optimizing above mentioned goals.

    MobilS: TC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    Christian Kluge, Stefan Schuster, Diana Schramm

    Statistics instead of Stopover

    Range Predictionc for Electric Vehicles

    Operations Research Proceedings 2016

    2017

    MobilF: Angewandte Informatik

    Zeitschriftenartikel

    Peter Sperber, Katrin Juds, Stefan Schuster, Ariane Hartmann, Diana Schramm

    Entwicklung und Einsatz des Optimierten Reichweitenmodells im Verbundprojekt E-WALD

    Zeitschrift für die gesamte Wertschöpfungskette Automobilwirtschaft (ZfAW), pp. 53-59

    2015