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E-Mobility as a Challenge for New ICT Solutions in the Car Industry

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7173)

Abstract

Future mobility scenarios show a continuous gain in market shares of electric vehicles (EVs) [1]. However, both speed and magnitude of EV market penetration depend on the evolution of critical success factors. Regulatory policy, e.g. CO2 emission targets, and hard constraints like peak–of–oil are some of the factors positively influencing EV market penetration [1]. In contrary, a partial mismatch of consumer expectations and EV realities exists [2], which negatively influences EV market success. Consumer expectations have been co-created with combustion engine vehicles over 125 years. Mostly price and relative resource shortage of EVs are perceived by consumers as a major entry barrier [3].

Breaking the barrier is a question of resource allocation. The resource shortage can be resolved either physically, e.g. by improving energy density of batteries, or by the means of intelligent services such as smart charging, energy routing, car and ride sharing. Both EV and infrastructure resources such as charging stations can be managed temporally, spatially and energetically so that the consumer does not perceive them as being constraint.

This paper addresses the challenge of intelligent resource coordination both from a formal modelling perspective and a value–added–service perspective. Firstly, it presents a formal ICT [4] based modelling approach, which is developed within the EU–funded project ASCENS [5]. Secondly, it presents an ICT based value–added–service, namely the EV Daily Travel Planning Service, which has been designed for user–centric resource coordination in the EV domain.

Keywords

  • Service Component
  • Travel Modality
  • Mobility Scenario
  • User Schedule
  • Infrastructure Resource

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. McKinsey: Transforming the powertrain value chain - a portfolio challenge (January 2011)

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  2. Deloitte: Unplugged: Electric vehicle realities versus consumer expectations (September 2011)

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  6. Hoch, N., Werther, B., Bensler, H.-P., Masuch, N., Lützenberger, M., Hessler, A., Albayrak, S., Siegwart, R.Y.: A User-Centric Approach for Efficient Daily Mobility Planning in E-Vehicle Infrastructure Networks. In: Advanced Microsystems for Automotive Applications 2011 (2011)

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  11. MatSim - Multi-Agent Transport Simulation Toolkit, http://www.matsim.org/

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Werther, B., Hoch, N. (2012). E-Mobility as a Challenge for New ICT Solutions in the Car Industry. In: Bruni, R., Sassone, V. (eds) Trustworthy Global Computing. TGC 2011. Lecture Notes in Computer Science, vol 7173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30065-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-30065-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30064-6

  • Online ISBN: 978-3-642-30065-3

  • eBook Packages: Computer ScienceComputer Science (R0)