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Determination of the Number of Required Charging Stations on a German Motorway Based on Real Traffic Data and Discrete Event-Based Simulation

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  • Witt Andreas

    (University of Fulda, Department of Business, Leipziger Straße 123, 36037 Fulda, Germany)

Abstract

To make travelling with electric vehicles (EVs) over long distances as convenient as travelling with traditional vehicles, charging stations along motorways are necessary. Furthermore, waiting times for free charging points must be short to enable a fast onward journey, and this also on days with heavy traffic volumes. To determine the required number of charging stations in more detail, a model was created that simulates the process of arriving and leaving cars at a charging park based on real traffic data. For the traffic data, a location and date in the Munich region were chosen that represent a peak demand and thus a “worst case” scenario. The ability to cover such scenarios as well seems to be important because otherwise severe congestion with long waiting times would appear on days with heavy traffic, which would make the use of EVs very unattractive. It turned out that 150 to 600 charging stations – depending on the considered scenario – would be necessary to charge proportions of 10% to 20% of all passing cars.

Suggested Citation

  • Witt Andreas, 2023. "Determination of the Number of Required Charging Stations on a German Motorway Based on Real Traffic Data and Discrete Event-Based Simulation," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 1-11, January.
  • Handle: RePEc:vrs:logitl:v:14:y:2023:i:1:p:1-11:n:3
    DOI: 10.2478/logi-2023-0001
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    References listed on IDEAS

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    1. Miguel Campaña & Esteban Inga & Jorge Cárdenas, 2021. "Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities," Energies, MDPI, vol. 14(16), pages 1-16, August.
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    3. Hung, Ying-Chao & PakHai Lok, Horace & Michailidis, George, 2022. "Optimal routing for electric vehicle charging systems with stochastic demand: A heavy traffic approximation approach," European Journal of Operational Research, Elsevier, vol. 299(2), pages 526-541.
    4. Haoming Liu & Wenqian Yin & Xiaoling Yuan & Man Niu, 2018. "Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station," Sustainability, MDPI, vol. 10(5), pages 1-20, April.
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