IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v170y2023ics0965856423000447.html
   My bibliography  Save this article

Uncertainty of available range in explaining the charging choice behavior of BEV users

Author

Listed:
  • Li, Hao
  • Yu, Lu
  • Chen, Yu
  • Tu, Huizhao
  • Zhang, Jun

Abstract

Available range (AR) uncertainty is prevalent in battery electric vehicles (BEVs). AR depends on traffic conditions, weather conditions, road conditions, driving style, etc. This study aims to examine the role of AR uncertainty in BEV users’ en-route charging and charging route choice behavior. A stated preference survey is designed and conducted to explore the two consecutive choice behaviors: (1) en-route charging and (2) charging route choice. Four model specifications for en-route charging and three for charging route choice are defined. AR uncertainty is, for the first time, considered in explaining en-route charging choice behavior, in addition to the conventional choice attributes such as travel time, charging duration, initial AR, average AR, etc. Socio-demographic and vehicle-related factors are also considered in the behavioral modeling. Furthermore, random parameters logit with error components model is utilized to capture the full panel effects. Results indicate that AR uncertainty significantly affects users’ en-route charging choice behavior, thus being indispensable in behavioral modeling. In addition, average AR can modify the association between AR uncertainty and choice decision. Demand for en-route charging will be overestimated when AR uncertainty is not considered. Furthermore, there is considerable inter-respondentand intra-respondent heterogeneity in the en-route charging choice. The effect of AR uncertainty is stronger for female and high-income BEV users. The findings will contribute substantially to better en-route charging demand estimation and optimal deployment of public charging stations, particularly for medium- to long-distance trips.

Suggested Citation

  • Li, Hao & Yu, Lu & Chen, Yu & Tu, Huizhao & Zhang, Jun, 2023. "Uncertainty of available range in explaining the charging choice behavior of BEV users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    • Handle: RePEc:eee:transa:v:170:y:2023:i:c:s0965856423000447
    DOI: 10.1016/j.tra.2023.103624
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423000447
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2023.103624?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. Langbroek, Joram H.M. & Franklin, Joel P. & Susilo, Yusak O., 2017. "When do you charge your electric vehicle? A stated adaptation approach," Energy Policy, Elsevier, vol. 108(C), pages 565-573.
    2. Tu, Huizhao & Li, Hao & van Lint, Hans & van Zuylen, Henk, 2012. "Modeling travel time reliability of freeways using risk assessment techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1528-1540.
    3. van Lint, J.W.C. & van Zuylen, Henk J. & Tu, H., 2008. "Travel time unreliability on freeways: Why measures based on variance tell only half the story," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 258-277, January.
    4. Li, Hao & Tu, Huizhao & Hensher, David A., 2016. "Integrating the mean–variance and scheduling approaches to allow for schedule delay and trip time variability under uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 151-163.
    5. Li, Hao & Gao, Kun & Tu, Huizhao, 2017. "Variations in mode-specific valuations of travel time reliability and in-vehicle crowding: Implications for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 250-263.
    6. Xu, Min & Meng, Qiang & Liu, Kai & Yamamoto, Toshiyuki, 2017. "Joint charging mode and location choice model for battery electric vehicle users," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 68-86.
    7. Davidov, Sreten & Pantoš, Miloš, 2017. "Planning of electric vehicle infrastructure based on charging reliability and quality of service," Energy, Elsevier, vol. 118(C), pages 1156-1167.
    8. Zheng Li & David Hensher, 2013. "Behavioural implications of preferences, risk attitudes and beliefs in modelling risky travel choice with travel time variability," Transportation, Springer, vol. 40(3), pages 505-523, May.
    9. María Yáñez & Elisabetta Cherchi & Benjamin Heydecker & Juan de Dios Ortúzar, 2011. "On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates," Networks and Spatial Economics, Springer, vol. 11(3), pages 393-418, September.
    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, Kai & Zhao, Lei, 2024. "The impact of new energy transportation means on China's food import," Research in Transportation Economics, Elsevier, vol. 103(C).
    2. Umm e Hanni & Toshiyuki Yamamoto & Toshiyuki Nakamura, 2024. "An Analysis of Electric Vehicle Charging Intentions in Japan," Sustainability, MDPI, vol. 16(3), pages 1-22, January.

    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. Li, Hao & Gao, Kun & Tu, Huizhao, 2017. "Variations in mode-specific valuations of travel time reliability and in-vehicle crowding: Implications for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 250-263.
    2. Sjoerd van der Spoel & Chintan Amrit & Jos van Hillegersberg, 2017. "Predictive analytics for truck arrival time estimation: a field study at a European distribution centre," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5062-5078, September.
    3. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    4. Muriel-Villegas, Juan E. & Alvarez-Uribe, Karla C. & Patiño-Rodríguez, Carmen E. & Villegas, Juan G., 2016. "Analysis of transportation networks subject to natural hazards – Insights from a Colombian case," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 151-165.
    5. Fu, Jianhua & Zhang, Yongqing, 2020. "Valuation of travel time reliability: Considering the traveler's adaptive expectation with an indifference band on daily trip duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 337-353.
    6. Zhang, Yue & Zhang, Qi & Farnoosh, Arash & Chen, Siyuan & Li, Yan, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Energy, Elsevier, vol. 169(C), pages 844-853.
    7. Natascia Andrenacci & Roberto Ragona & Antonino Genovese, 2020. "Evaluation of the Instantaneous Power Demand of an Electric Charging Station in an Urban Scenario," Energies, MDPI, vol. 13(11), pages 1-19, May.
    8. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    9. Shi, Xiao & Pan, Jian & Wang, Hewu & Cai, Hua, 2019. "Battery electric vehicles: What is the minimum range required?," Energy, Elsevier, vol. 166(C), pages 352-358.
    10. Watanabe, Hajime & Maruyama, Takuya, 2023. "A Bayesian instrumental variable model for multinomial choice with correlated alternatives," Journal of choice modelling, Elsevier, vol. 46(C).
    11. Hong Gao & Kai Liu & Xinchao Peng & Cheng Li, 2020. "Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands," Energies, MDPI, vol. 13(8), pages 1-16, April.
    12. Tu, Huizhao & Li, Hao & van Lint, Hans & van Zuylen, Henk, 2012. "Modeling travel time reliability of freeways using risk assessment techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1528-1540.
    13. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    14. Hu, Dingding & Zhou, Kaile & Li, Fangyi & Ma, Dawei, 2022. "Electric vehicle user classification and value discovery based on charging big data," Energy, Elsevier, vol. 249(C).
    15. Krier, Betty & Liu, Chia-Mei & McNamara, Brian & Sharpe, Jerrod, 2014. "Individual freight effects, capacity utilization, and Amtrak service quality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 163-175.
    16. Csiszár, Csaba & Csonka, Bálint & Földes, Dávid & Wirth, Ervin & Lovas, Tamás, 2020. "Location optimisation method for fast-charging stations along national roads," Journal of Transport Geography, Elsevier, vol. 88(C).
    17. Stefanie Peer & Carl Koopmans & Erik T. Verhoef, 2010. "Predicting Travel Time Variability for Cost-Benefit Analysis," Tinbergen Institute Discussion Papers 10-071/3, Tinbergen Institute.
    18. Hsieh, Hsu-Sheng, 2020. "Transport policy evaluation based on elasticity analysis with social interactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 273-296.
    19. Chengxiang Zhuge & Chunfu Shao & Xia Li, 2019. "Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China," Energies, MDPI, vol. 12(16), pages 1-21, August.
    20. Soriguera, Francesc, 2014. "On the value of highway travel time information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 294-310.

    More about this item

    Statistics

    Access and download statistics

    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:transa:v:170:y:2023:i:c:s0965856423000447. 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/wps/find/journaldescription.cws_home/547/description#description .

    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.