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Electric Vehicle Charging Process and Parking Guidance App

Author

Listed:
  • Gonçalo Alface

    (Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR-IUL, 1649-026 Lisboa, Portugal)

  • João C. Ferreira

    (Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR-IUL, 1649-026 Lisboa, Portugal
    INOV INESC Inovação—Instituto de Novas Tecnologias, 1000-029 Lisboa, Portugal)

  • Rúben Pereira

    (Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR-IUL, 1649-026 Lisboa, Portugal)

Abstract

This research work presents an information system to handle the problem of real-time guidance towards free charging slot in a city using past date and prediction and collaborative algorithms since there is no real-time system available to provide information if a charging spot is free or occupied. We explore the prediction approach using past data correlated with weather conditions. This approach will help the driver in the daily use of his electric vehicle, minimizing the problem of range anxiety, provide guidance towards charging spots with a probability value of being available for charging in a context for the app and smart cities. This work handles the uncertainty of the drivers to get a suitable and vacant place at a charging station because missing real-time information from the system and also during the driving process towards the free charging spot can be taken. We introduce a framework to allow collaboration and prediction process using past related data.

Suggested Citation

  • Gonçalo Alface & João C. Ferreira & Rúben Pereira, 2019. "Electric Vehicle Charging Process and Parking Guidance App," Energies, MDPI, vol. 12(11), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2123-:d:236772
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    Citations

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    Cited by:

    1. Karol Tucki & Olga Orynycz & Mateusz Mitoraj-Wojtanek, 2020. "Perspectives for Mitigation of CO 2 Emission due to Development of Electromobility in Several Countries," Energies, MDPI, vol. 13(16), pages 1-24, August.
    2. Jun Li & Sifan Wu & Xiaoman Feng, 2021. "Optimization of On-Street Parking Charges Based on Price Elasticity of the Expected Perceived Parking Cost," Sustainability, MDPI, vol. 13(10), pages 1-13, May.
    3. Luis B. Elvas & Joao C Ferreira, 2021. "Intelligent Transportation Systems for Electric Vehicles," Energies, MDPI, vol. 14(17), pages 1-9, September.

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