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Proposing a more comprehensive future total cost of ownership estimation framework for electric vehicles

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  • van Velzen, Arjan
  • Annema, Jan Anne
  • van de Kaa, Geerten
  • van Wee, Bert

Abstract

Different scholars have tried to forecast the total cost of ownership (TCO) of electric vehicles (EVs). These studies use different implicit assumptions. This research aims to develop a more comprehensive EV TCO forecasting framework based on a combination of literature review and interviews. The main finding is a framework of 34 factors that influence the future TCO of EVs. By using scenarios, we noticed that the ‘profit margin’ factor seems to be underestimated in current TCO literature. Assuming that in the years to come EV producers want to recoup their investments, we showed that even in a future with much learning and scale effects this does not imply that the TCO of a specific EV will become much lower compared to the TCO of a comparable internal combustion engine vehicle (ICEV). For policymakers this implies that if they want to stimulate the use of EVs they might also need to put policies (e.g. tax policies) in place to increase the TCO of ICEVs. Another policy implication of our analysis is that EV stimulating policies seem to require a long-term effort. EV manufacturers and dealers might be tempted (or even ‘forced’ by shareholders) to increase EV prices rather quickly.

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  • van Velzen, Arjan & Annema, Jan Anne & van de Kaa, Geerten & van Wee, Bert, 2019. "Proposing a more comprehensive future total cost of ownership estimation framework for electric vehicles," Energy Policy, Elsevier, vol. 129(C), pages 1034-1046.
    • Handle: RePEc:eee:enepol:v:129:y:2019:i:c:p:1034-1046
    DOI: 10.1016/j.enpol.2019.02.071
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    Cited by:

    1. Moon, Saedaseul & Lee, Deok-Joo, 2019. "An optimal electric vehicle investment model for consumers using total cost of ownership: A real option approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    2. Ouyang, Danhua & Zhou, Shen & Ou, Xunmin, 2021. "The total cost of electric vehicle ownership: A consumer-oriented study of China's post-subsidy era," Energy Policy, Elsevier, vol. 149(C).
    3. Guo, Hongqiang & Hou, Daizheng & Du, Shangye & Zhao, Ling & Wu, Jian & Yan, Ning, 2020. "A driving pattern recognition-based energy management for plug-in hybrid electric bus to counter the noise of stochastic vehicle mass," Energy, Elsevier, vol. 198(C).
    4. Zhou, Kaile & Cheng, Lexin & Lu, Xinhui & Wen, Lulu, 2020. "Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices," Applied Energy, Elsevier, vol. 276(C).
    5. Scorrano, Mariangela & Danielis, Romeo & Giansoldati, Marco, 2020. "Dissecting the total cost of ownership of fully electric cars in Italy: The impact of annual distance travelled, home charging and urban driving," Research in Transportation Economics, Elsevier, vol. 80(C).
    6. Hao, Xu & Lin, Zhenhong & Wang, Hewu & Ou, Shiqi & Ouyang, Minggao, 2020. "Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach," Applied Energy, Elsevier, vol. 275(C).
    7. Schwab, Julia & Sölch, Christian & Zöttl, Gregor, 2022. "Electric Vehicle Cost in 2035: The impact of market penetration and charging strategies," Energy Economics, Elsevier, vol. 114(C).

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