IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v122y2018icp162-168.html
   My bibliography  Save this article

Empirical analysis of electric vehicle fast charging under cold temperatures

Author

Listed:
  • Motoaki, Yutaka
  • Yi, Wenqi
  • Salisbury, Shawn

Abstract

This paper presents an empirical analysis of the effects of temperature on Direct Current Fast Charger (DCFC) charging rate and discusses the impact of such effects on wider adoptions of electric vehicles (EVs). The authors conducted statistical analysis on the effects of temperature and constructed an electric vehicle charging model that can show the dynamics of DCFC charging process under different temperatures. The results indicate that DCFC charging rate can deteriorate considerably in cold temperatures. These findings may be used as a reference to identify and assess the regions that may suffer from slow charging. The problems associated with temperature effects on DCFC charging deserve greater attention as electrification of motor vehicles progresses and DCFC usage increases in the future.

Suggested Citation

  • Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
  • Handle: RePEc:eee:enepol:v:122:y:2018:i:c:p:162-168
    DOI: 10.1016/j.enpol.2018.07.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421518304828
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2018.07.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Motoaki, Yutaka & Shirk, Matthew G., 2017. "Consumer behavioral adaption in EV fast charging through pricing," Energy Policy, Elsevier, vol. 108(C), pages 178-183.
    2. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    3. Bryden, Thomas S. & Hilton, George & Cruden, Andrew & Holton, Tim, 2018. "Electric vehicle fast charging station usage and power requirements," Energy, Elsevier, vol. 152(C), pages 322-332.
    4. Bernardo, Valeria & Borrell, Joan-Ramon & Perdiguero, Jordi, 2016. "Fast charging stations: Simulating entry and location in a game of strategic interaction," Energy Economics, Elsevier, vol. 60(C), pages 293-305.
    5. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
    6. Zenginis, Ioannis & Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Analysis and quality of service evaluation of a fast charging station for electric vehicles," Energy, Elsevier, vol. 112(C), pages 669-678.
    7. Wang, Yusheng & Huang, Yongxi & Xu, Jiuping & Barclay, Nicole, 2017. "Optimal recharging scheduling for urban electric buses: A case study in Davis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 115-132.
    8. Yang, Woosuk, 2018. "A user-choice model for locating congested fast charging stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 189-213.
    9. Schroeder, Andreas & Traber, Thure, 2012. "The economics of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 43(C), pages 136-144.
    10. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    11. Pol Olivella-Rosell & Roberto Villafafila-Robles & Andreas Sumper & Joan Bergas-Jané, 2015. "Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks," Energies, MDPI, vol. 8(5), pages 1-28, May.
    12. Morrissey, Patrick & Weldon, Peter & O’Mahony, Margaret, 2016. "Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour," Energy Policy, Elsevier, vol. 89(C), pages 257-270.
    13. Liu, Jian, 2012. "Electric vehicle charging infrastructure assignment and power grid impacts assessment in Beijing," Energy Policy, Elsevier, vol. 51(C), pages 544-557.
    14. Jaguemont, J. & Boulon, L. & Dubé, Y., 2016. "A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures," Applied Energy, Elsevier, vol. 164(C), pages 99-114.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Ma, Shao-Chao & Fan, Ying, 2020. "A deployment model of EV charging piles and its impact on EV promotion," Energy Policy, Elsevier, vol. 146(C).
    2. Muhammad Asim & Muhammad Usman & Muhammad Salman Abbasi & Saad Ahmad & M. A. Mujtaba & Manzoore Elahi M. Soudagar & Abdullah Mohamed, 2022. "Estimating the Long-Term Effects of National and International Sustainable Transport Policies on Energy Consumption and Emissions of Road Transport Sector of Pakistan," Sustainability, MDPI, vol. 14(9), pages 1-19, May.
    3. 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).
    4. Weixing Liu & Hongtao Yi, 2020. "What Affects the Diffusion of New Energy Vehicles Financial Subsidy Policy? Evidence from Chinese Cities," IJERPH, MDPI, vol. 17(3), pages 1-15, January.
    5. Amin Aghalari & Darweesh Ehssan Salamah & Carlos Marino & Mohammad Marufuzzaman, 2023. "Electric vehicles fast charger location-routing problem under ambient temperature," Annals of Operations Research, Springer, vol. 324(1), pages 721-759, May.
    6. Michéle Weisbach & Tobias Schneider & Dominik Maune & Heiko Fechtner & Utz Spaeth & Ralf Wegener & Stefan Soter & Benedikt Schmuelling, 2021. "Intelligent Multi-Vehicle DC/DC Charging Station Powered by a Trolley Bus Catenary Grid," Energies, MDPI, vol. 14(24), pages 1-21, December.
    7. 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.
    8. Haber, Marc & Azaïs, Philippe & Genies, Sylvie & Raccurt, Olivier, 2023. "Stress factor identification and Risk Probabilistic Number (RPN) analysis of Li-ion batteries based on worldwide electric vehicle usage," Applied Energy, Elsevier, vol. 343(C).
    9. Makeen, Peter & Ghali, Hani A. & Memon, Saim & Duan, Fang, 2022. "Impacts of electric vehicle fast charging under dynamic temperature and humidity: Experimental and theoretically validated model analyses," Energy, Elsevier, vol. 261(PB).
    10. Li, Niansi & Liu, Xiaoyong & Yu, Bendong & Li, Liang & Xu, Jianqiang & Tan, Qiong, 2021. "Study on the environmental adaptability of lithium-ion battery powered UAV under extreme temperature conditions," Energy, Elsevier, vol. 219(C).
    11. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Anamarija Falkoni & Antun Pfeifer & Goran Krajačić, 2020. "Vehicle-to-Grid in Standard and Fast Electric Vehicle Charging: Comparison of Renewable Energy Source Utilization and Charging Costs," Energies, MDPI, vol. 13(6), pages 1-22, March.
    3. Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    4. Motoaki, Yutaka & Shirk, Matthew G., 2017. "Consumer behavioral adaption in EV fast charging through pricing," Energy Policy, Elsevier, vol. 108(C), pages 178-183.
    5. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    6. Arlt, Marie-Louise & Astier, Nicolas, 2023. "Do retail businesses have efficient incentives to invest in public charging stations for electric vehicles?," Energy Economics, Elsevier, vol. 124(C).
    7. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
    8. Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    9. Pemberton, Simon & Nobajas, Alexandre & Waller, Richard, 2021. "Rapid charging provision, multiplicity and battery electric vehicle (BEV) mobility in the UK," Journal of Transport Geography, Elsevier, vol. 95(C).
    10. Wolbertus, Rick & Kroesen, Maarten & van den Hoed, Robert & Chorus, Caspar, 2018. "Fully charged: An empirical study into the factors that influence connection times at EV-charging stations," Energy Policy, Elsevier, vol. 123(C), pages 1-7.
    11. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
    12. Yuan-Yuan Wang & Yuan-Ying Chi & Jin-Hua Xu & Jia-Lin Li, 2021. "Consumer Preferences for Electric Vehicle Charging Infrastructure Based on the Text Mining Method," Energies, MDPI, vol. 14(15), pages 1-20, July.
    13. Mu Li & Yingqi Liu & Weizhong Yue, 2022. "Evolutionary Game of Actors in China’s Electric Vehicle Charging Infrastructure Industry," Energies, MDPI, vol. 15(23), pages 1-20, November.
    14. Lukas Lanz & Bessie Noll & Tobias S. Schmidt & Bjarne Steffen, 2022. "Comparing the levelized cost of electric vehicle charging options in Europe," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    15. Tian Wu & Bohan Zeng & Yali He & Xin Tian & Xunmin Ou, 2017. "Sustainable Governance for the Opened Electric Vehicle Charging and Upgraded Facilities Market," Sustainability, MDPI, vol. 9(11), pages 1-22, November.
    16. Tao, Ye & Huang, Miaohua & Chen, Yupu & Yang, Lan, 2020. "Orderly charging strategy of battery electric vehicle driven by real-world driving data," Energy, Elsevier, vol. 193(C).
    17. Yang, Woosuk, 2018. "A user-choice model for locating congested fast charging stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 189-213.
    18. Neil Stephen Lopez & Adrian Allana & Jose Bienvenido Manuel Biona, 2021. "Modeling Electric Vehicle Charging Demand with the Effect of Increasing EVSEs: A Discrete Event Simulation-Based Model," Energies, MDPI, vol. 14(13), pages 1-15, June.
    19. Chen, Yu & Lin, Boqiang, 2022. "Are consumers in China’s major cities happy with charging infrastructure for electric vehicles?," Applied Energy, Elsevier, vol. 327(C).
    20. Wang, Bin & Wang, Shifeng & Tang, Yuanyuan & Tsang, Chi-Wing & Dai, Jinchuan & Leung, Michael K.H. & Lu, Xiao-Ying, 2019. "Micro/nanostructured MnCo2O4.5 anodes with high reversible capacity and excellent rate capability for next generation lithium-ion batteries," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:122:y:2018:i:c:p:162-168. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.