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Large-scale deployment of electric taxis in Beijing: A real-world analysis

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  • Zou, Yuan
  • Wei, Shouyang
  • Sun, Fengchun
  • Hu, Xiaosong
  • Shiao, Yaojung

Abstract

The national and municipal government of China enacted a series of regulations and policies to stimulate/promote the development of new energy vehicles, in order to mitigate the increasingly serious carbon emissions, environmental pollution, and energy shortage. As a large metropolitan and populated city subject to the notorious air pollution, Beijing has been making a remarkable progress in the large-scale demonstration of new energy vehicles in recent years, which could result in a significant impact on both transport and electricity sectors. As a result, there is an urgent necessity to study the characteristics of the large-scale new energy vehicles adoption for a deep understanding of operational status (e.g., energy consumption and battery charging patterns) and benefits, as well as charging facilities. Based on the operational data collected from realistic electric-taxi demonstration in Beijing, the driver behavior and charging characteristics are examined in this paper. The energy consumption and efficiency of two representative electric-taxi platforms are compared, and the influence of the driving schedules is discussed. The results show that the average driving distance per day of these electric taxes is 117.98 km, and 92% of drivers recharge their cars twice per day. Further study shows that the drivers make two trips per day, and the two peaks in the distribution of departure and arrival times coincide with the rush hour in the morning and evening. The taxi recharge duration is largely influenced by the charging power. Generally, the associated battery SOC (state of charge) swing is between 40% and 100%. By evaluating the energy consumption of 282 trips recorded in 2013 and 2014, we find that the two platforms have similar energy efficiency. The micro-trips method is utilized to probe the correlation of energy consumption and average speed.

Suggested Citation

  • Zou, Yuan & Wei, Shouyang & Sun, Fengchun & Hu, Xiaosong & Shiao, Yaojung, 2016. "Large-scale deployment of electric taxis in Beijing: A real-world analysis," Energy, Elsevier, vol. 100(C), pages 25-39.
    • Handle: RePEc:eee:energy:v:100:y:2016:i:c:p:25-39
    DOI: 10.1016/j.energy.2016.01.062
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    7. 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.
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    10. Michael Bosello & Carlo Falcomer & Claudio Rossi & Giovanni Pau, 2023. "To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders," Energies, MDPI, vol. 16(6), pages 1-17, March.
    11. Tao, Ye & Huang, Miaohua & Yang, Lan, 2018. "Data-driven optimized layout of battery electric vehicle charging infrastructure," Energy, Elsevier, vol. 150(C), pages 735-744.
    12. Gong, Huiming & Zou, Yuan & Yang, Qingkai & Fan, Jie & Sun, Fengchun & Goehlich, Dietmar, 2018. "Generation of a driving cycle for battery electric vehicles：A case study of Beijing," Energy, Elsevier, vol. 150(C), pages 901-912.
    13. Hicham El Hadraoui & Mourad Zegrari & Fatima-Ezzahra Hammouch & Nasr Guennouni & Oussama Laayati & Ahmed Chebak, 2022. "Design of a Customizable Test Bench of an Electric Vehicle Powertrain for Learning Purposes Using Model-Based System Engineering," Sustainability, MDPI, vol. 14(17), pages 1-22, September.
    14. Demeulenaere, Xavier, 2019. "The use of automotive fleets to support the diffusion of Alternative Fuel Vehicles: A Rapid Evidence Assessment of barriers and decision mechanisms," Research in Transportation Economics, Elsevier, vol. 76(C).
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    16. Zhang, Jin & Wang, Zhenpo & Liu, Peng & Zhang, Zhaosheng, 2020. "Energy consumption analysis and prediction of electric vehicles based on real-world driving data," Applied Energy, Elsevier, vol. 275(C).
    17. Calearo, Lisa & Marinelli, Mattia & Ziras, Charalampos, 2021. "A review of data sources for electric vehicle integration studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    18. Yang, Jie & Dong, Jing & Hu, Liang, 2018. "Design government incentive schemes for promoting electric taxis in China," Energy Policy, Elsevier, vol. 115(C), pages 1-11.
    19. 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).
    20. Zhao, Yinan & Wen, Yifan & Wang, Fang & Tu, Wei & Zhang, Shaojun & Wu, Ye & Hao, Jiming, 2023. "Feasibility, economic and carbon reduction benefits of ride-hailing vehicle electrification by coupling travel trajectory and charging infrastructure data," Applied Energy, Elsevier, vol. 342(C).
    21. Ruisheng Wang & Qiang Xing & Zhong Chen & Ziqi Zhang & Bo Liu, 2022. "Modeling and Analysis of Electric Vehicle User Behavior Based on Full Data Chain Driven," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    22. Zhang, Junxia & Li, Xingmei & Jia, Dongqing & Zhou, Yuexin, 2023. "A Bi-level programming for union battery swapping stations location-routing problem under joint distribution and cost allocation," Energy, Elsevier, vol. 272(C).
    23. Yang, W.H. & Wong, R.C.P. & Szeto, W.Y., 2018. "Modeling the acceptance of taxi owners and drivers to operate premium electric taxis: Policy insights into improving taxi service quality and reducing air pollution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 581-593.
    24. Wilfredo F. Yushimito & Sebastian Moreno & Daniela Miranda, 2023. "The Potential of Battery Electric Taxis in Santiago de Chile," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    25. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Zhang, Zhaosheng & Dorrell, David G. & Li, Xiaohui, 2022. "Battery electric vehicle usage pattern analysis driven by massive real-world data," Energy, Elsevier, vol. 250(C).

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