IDEAS home Printed from https://ideas.repec.org/r/eee/enepol/v123y2018icp1-7.html
   My bibliography  Save this item

Fully charged: An empirical study into the factors that influence connection times at EV-charging stations

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Wolff, Stefanie & Madlener, Reinhard, 2019. "Charged up? Preferences for Electric Vehicle Charging and Implications for Charging Infrastructure Planning," FCN Working Papers 3/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  2. Milan Straka & Rui Carvalho & Gijs van der Poel & v{L}ubov{s} Buzna, 2020. "Explaining the distribution of energy consumption at slow charging infrastructure for electric vehicles from socio-economic data," Papers 2006.01672, arXiv.org, revised Jun 2020.
  3. Xiong Yang & Chengxiang Zhuge & Chunfu Shao & Runhang Guo & Andrew Tin Chak Wong & Xiaoyu Zhang & Mingdong Sun & Pinxi Wang & Shiqi Wang, 2025. "Dominant charging location choice of commuters and non-commuters: a big data approach," Transportation, Springer, vol. 52(2), pages 439-466, April.
  4. Wang, Ning & Tian, Hangqi & Wu, Huahua & Liu, Qiaoqian & Luan, Jie & Li, Yuan, 2023. "Cost-oriented optimization of the location and capacity of charging stations for the electric Robotaxi fleet," Energy, Elsevier, vol. 263(PC).
  5. Alexandre Lucas & Ricardo Barranco & Nazir Refa, 2019. "EV Idle Time Estimation on Charging Infrastructure, Comparing Supervised Machine Learning Regressions," Energies, MDPI, vol. 12(2), pages 1-17, January.
  6. Andrea La Nauze & Lana Friesen & Kai Li Lim & Flavio Menezes & Lionel Page & Thara Philip & Jake Whitehead, 2024. "Can Electric Vehicles Aid the Renewable Transition? Evidence from a Field Experiment Incentivising Midday Charging," CESifo Working Paper Series 11386, CESifo.
  7. Einolander, Johannes & Lahdelma, Risto, 2022. "Multivariate copula procedure for electric vehicle charging event simulation," Energy, Elsevier, vol. 238(PA).
  8. Wolbertus, Rick & van den Hoed, Robert & Kroesen, Maarten & Chorus, Caspar, 2021. "Charging infrastructure roll-out strategies for large scale introduction of electric vehicles in urban areas: An agent-based simulation study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 262-285.
  9. Luis Oliveira & Arun Ulahannan & Matthew Knight & Stewart Birrell, 2020. "Wireless Charging of Electric Taxis: Understanding the Facilitators and Barriers to Its Introduction," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
  10. Wolff, Stefanie & Madlener, Reinhard, 2020. "Willing to Pay? Spatial Heterogeneity of e-Vehicle Charging Preferences in Germany," FCN Working Papers 9/2020, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  11. Einolander, Johannes & Lahdelma, Risto, 2022. "Explicit demand response potential in electric vehicle charging networks: Event-based simulation based on the multivariate copula procedure," Energy, Elsevier, vol. 256(C).
  12. Siddique, Choudhury & Afifah, Fatima & Guo, Zhaomiao & Zhou, Yan, 2022. "Data mining of plug-in electric vehicles charging behavior using supply-side data," Energy Policy, Elsevier, vol. 161(C).
  13. Christopher Hecht & Jan Figgener & Xiaohui Li & Lei Zhang & Dirk Uwe Sauer, 2023. "Standard Load Profiles for Electric Vehicle Charging Stations in Germany Based on Representative, Empirical Data," Energies, MDPI, vol. 16(6), pages 1-21, March.
  14. Zhang, Zhen & Zhu, Yuhao & Zhang, Qi & Cui, Naxin & Shang, Yunlong, 2024. "Multi-cycle charging information guided state of health estimation for lithium-ion batteries based on pre-trained large language model," Energy, Elsevier, vol. 313(C).
  15. Graham Town & Seyedfoad Taghizadeh & Sara Deilami, 2022. "Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning," Energies, MDPI, vol. 15(4), pages 1-30, February.
  16. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
  17. Zhou, Xizhen & Cai, Yutong & Meng, Qiang & Ji, Yanjie, 2025. "A user behavior and reinforcement learning based dynamic pricing method for idle connection time reduction at charging stations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 192(C).
  18. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
  19. Lagomarsino, Maria & van der Kam, Mart & Parra, David & Hahnel, Ulf J.J., 2022. "Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging," Energy Policy, Elsevier, vol. 162(C).
  20. Philipp A. Friese & Wibke Michalk & Markus Fischer & Cornelius Hardt & Klaus Bogenberger, 2021. "Charging Point Usage in Germany—Automated Retrieval, Analysis, and Usage Types Explained," Sustainability, MDPI, vol. 13(23), pages 1-26, November.
  21. Steffen Limmer, 2019. "Dynamic Pricing for Electric Vehicle Charging—A Literature Review," Energies, MDPI, vol. 12(18), pages 1-24, September.
  22. Huang, Bing & Meijssen, Aart Gerard & Annema, Jan Anne & Lukszo, Zofia, 2021. "Are electric vehicle drivers willing to participate in vehicle-to-grid contracts? A context-dependent stated choice experiment," Energy Policy, Elsevier, vol. 156(C).
  23. Helmus, Jurjen R. & Lees, Michael H. & van den Hoed, Robert, 2022. "A validated agent-based model for stress testing charging infrastructure utilization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 237-262.
  24. Simolin, Toni & Rauma, Kalle & Viri, Riku & Mäkinen, Johanna & Rautiainen, Antti & Järventausta, Pertti, 2021. "Charging powers of the electric vehicle fleet: Evolution and implications at commercial charging sites," Applied Energy, Elsevier, vol. 303(C).
  25. Budnitz, Hannah & Meelen, Toon & Schwanen, Tim, 2022. "Residential Neighbourhood Charging of Electric Vehicles: an exploration of user preferences," SocArXiv fsv7n, Center for Open Science.
  26. Wang, Shengyou & Zhuge, Chengxiang & Shao, Chunfu & Wang, Pinxi & Yang, Xiong & Wang, Shiqi, 2023. "Short-term electric vehicle charging demand prediction: A deep learning approach," Applied Energy, Elsevier, vol. 340(C).
  27. Liu, Meng & He, Sylvia Y., 2025. "E-taxi drivers' charging behavior: Effects of the built environment, temporal factors, and ridership," Journal of Transport Geography, Elsevier, vol. 123(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.