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Taxi trajectory data based fast-charging facility planning for urban electric taxi systems

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  • Wang, Hua
  • Zhao, De
  • Cai, Yutong
  • Meng, Qiang
  • Ong, Ghim Ping

Abstract

This study develops a taxi trajectory data based fast-charging facility planning model for an urban taxi system by considering battery degradation and vehicle heterogeneity in driving range. The developed model comprises three functional modules: (i) fast-charging location determination, (ii) fast-charging facility deployment (FCFD) and (iii) FCFD solution tuning. Under the FCFD module, charging demand prediction considering battery degradation and vehicle heterogeneity, charging demand allocation and charger configuration optimization are executed sequentially. The FCFD solution is tuned by an effective backward elimination method to find a more economic and practical planning solution where the minimal number of chargers at each station can be specified. A case study in Singapore is thoroughly conducted, and insightful policy implications are revealed: policy-makers could use the tuning mechanism to significantly save investment and reduce total waiting time for charging; overlooking battery degradation and vehicle heterogeneity will yield a biased electric taxi charging facility planning.

Suggested Citation

  • Wang, Hua & Zhao, De & Cai, Yutong & Meng, Qiang & Ong, Ghim Ping, 2021. "Taxi trajectory data based fast-charging facility planning for urban electric taxi systems," Applied Energy, Elsevier, vol. 286(C).
    • Handle: RePEc:eee:appene:v:286:y:2021:i:c:s0306261921000696
    DOI: 10.1016/j.apenergy.2021.116515
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    References listed on IDEAS

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    Cited by:

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    2. Jianxin Qin & Jing Qiu & Yating Chen & Tao Wu & Longgang Xiang, 2022. "Charging Stations Selection Using a Graph Convolutional Network from Geographic Grid," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
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    4. Pichamon Keawthong & Veera Muangsin & Chupun Gowanit, 2022. "Location Selection of Charging Stations for Electric Taxis: A Bangkok Case," Sustainability, MDPI, vol. 14(17), pages 1-23, September.
    5. 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.

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