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Prediction of Electric Vehicle Range: A Comprehensive Review of Current Issues and Challenges

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  • Bogdan Ovidiu Varga

    (Automotive Engineering and Transports Department, Technical University of Cluj-Napoca, RO-400641 Cluj Napoca, Romania)

  • Arsen Sagoian

    (Automotive Engineering and Transports Department, Technical University of Cluj-Napoca, RO-400641 Cluj Napoca, Romania)

  • Florin Mariasiu

    (Automotive Engineering and Transports Department, Technical University of Cluj-Napoca, RO-400641 Cluj Napoca, Romania)

Abstract

Electric vehicles (EV) are the immediate solution to drastically reducing pollutant emissions from the transport sector. There is a continuing increase in the number of EVs in use, but their widespread and massive acceptance by automotive consumers is related to the performance they can deliver. The most important feature here (a hot topic at present in EV research) is related to the possibility of providing a more accurate prediction of range. Range prediction is a complex problem because it depends on a lot of influence factors (internal, external, constant, variables) and the present paper aims to investigate the effect of these factors on the range of EVs. The results and aspects of current worldwide research on this theme are presented through the analysis of the main classes of influence factors: Vehicle design, the driver and the environment. Further, the weight and effect of each potential factor which influences EV range was analyzed by presenting current issues. An exhaustive and comprehensive analysis has made it possible to identify future research and development directions in the EV research field, resulting in massive future and immediate EV penetration in the automotive market.

Suggested Citation

  • Bogdan Ovidiu Varga & Arsen Sagoian & Florin Mariasiu, 2019. "Prediction of Electric Vehicle Range: A Comprehensive Review of Current Issues and Challenges," Energies, MDPI, vol. 12(5), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:946-:d:213084
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    References listed on IDEAS

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    1. Egbue, Ona & Long, Suzanna, 2012. "Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions," Energy Policy, Elsevier, vol. 48(C), pages 717-729.
    2. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    3. Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang & Mingwang Wang, 2018. "A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature," Energies, MDPI, vol. 11(9), pages 1-17, September.
    4. Franke, Thomas & Krems, Josef F., 2013. "Interacting with limited mobility resources: Psychological range levels in electric vehicle use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 48(C), pages 109-122.
    5. Cedric De Cauwer & Wouter Verbeke & Thierry Coosemans & Saphir Faid & Joeri Van Mierlo, 2017. "A Data-Driven Method for Energy Consumption Prediction and Energy-Efficient Routing of Electric Vehicles in Real-World Conditions," Energies, MDPI, vol. 10(5), pages 1-18, May.
    6. Björn Nykvist & Måns Nilsson, 2015. "Rapidly falling costs of battery packs for electric vehicles," Nature Climate Change, Nature, vol. 5(4), pages 329-332, April.
    7. Marco-Tulio F. Rodrigues & Ganguli Babu & Hemtej Gullapalli & Kaushik Kalaga & Farheen N. Sayed & Keiko Kato & Jarin Joyner & Pulickel M. Ajayan, 2017. "A materials perspective on Li-ion batteries at extreme temperatures," Nature Energy, Nature, vol. 2(8), pages 1-14, August.
    8. Wu, Geng & Inderbitzin, Alessandro & Bening, Catharina, 2015. "Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments," Energy Policy, Elsevier, vol. 80(C), pages 196-214.
    9. Eunil Park & Jooyoung Lim & Yongwoo Cho, 2018. "Understanding the Emergence and Social Acceptance of Electric Vehicles as Next-Generation Models for the Automobile Industry," Sustainability, MDPI, vol. 10(3), pages 1-13, March.
    10. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    11. David Jiménez & Sara Hernández & Jesús Fraile-Ardanuy & Javier Serrano & Rubén Fernández & Federico Álvarez, 2018. "Modelling the Effect of Driving Events on Electrical Vehicle Energy Consumption Using Inertial Sensors in Smartphones," Energies, MDPI, vol. 11(2), pages 1-23, February.
    12. McManus, M.C., 2012. "Environmental consequences of the use of batteries in low carbon systems: The impact of battery production," Applied Energy, Elsevier, vol. 93(C), pages 288-295.
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