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Planning station capacity and fleet size of one-way electric carsharing systems with continuous state of charge functions

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  • Huang, Kai
  • An, Kun
  • Correia, Gonçalo Homem de Almeida

Abstract

This paper presents a method for determining the deployment of one-way electric carsharing services within a designated region that maximizes the total profit of the operator. A mixed integer non-linear program model is built, with a strategic planning level that decides the fleet size and the station capacity and an operational level that decides on the required relocation operations. The state of charge (SOC) of the vehicles parked in one station is assumed to follow a continuous distribution. A rolling horizon method is used to optimize the operational decisions over the course of a day, considering demand fluctuations and the limited battery capacity of the vehicles. A golden section line search method and a shadow price algorithm are developed to optimize the fleet size and station capacity, with the results feeding back to the carsharing operations. To demonstrate the applicability of the formulated models and solution algorithms, a large-scale case study is conducted for Suzhou Industrial Park, China as the region of operation. A two-step verification method that combines an optimization model via tracking of individual vehicle SOC and a discrete event simulation, demonstrates the accuracy of the SOC distribution model. Managerial insights from the application are also presented.

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  • Huang, Kai & An, Kun & Correia, Gonçalo Homem de Almeida, 2020. "Planning station capacity and fleet size of one-way electric carsharing systems with continuous state of charge functions," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1075-1091.
    • Handle: RePEc:eee:ejores:v:287:y:2020:i:3:p:1075-1091
    DOI: 10.1016/j.ejor.2020.05.001
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    5. Golalikhani, Masoud & Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando & Antunes, António Pais, 2021. "Carsharing: A review of academic literature and business practices toward an integrated decision-support framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    6. Huang, Kai & An, Kun & Rich, Jeppe & Ma, Wanjing, 2020. "Vehicle relocation in one-way station-based electric carsharing systems: A comparative study of operator-based and user-based methods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
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    9. Katarzyna Turoń & Andrzej Kubik & Feng Chen, 2021. "Electric Shared Mobility Services during the Pandemic: Modeling Aspects of Transportation," Energies, MDPI, vol. 14(9), pages 1-19, May.
    10. Yang, Jie & Hu, Lu & Jiang, Yangsheng, 2022. "An overnight relocation problem for one-way carsharing systems considering employment planning, return restrictions, and ride sharing of temporary workers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
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    13. Huang, Kai & Zhou, Peng & Liu, Zhiyuan & Tang, Tianli & Zhang, Honggang & Jiang, Wei, 2024. "The calculation and distribution of CAV carbon emissions on urban transportation systems: A comparative analysis of renewable and non-renewable energy sources," Renewable Energy, Elsevier, vol. 230(C).
    14. Bansal, Vishal & Kumar, Deepak Prakash & Roy, Debjit & Subramanian, Shankar C., 2022. "Performance evaluation and optimization of design parameters for electric vehicle-sharing platforms by considering vehicle dynamics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    15. Bitencourt, Leonardo & Dias, Bruno & Soares, Tiago & Borba, Bruno & Quirós-Tortós, Jairo, 2023. "e-Carsharing siting and sizing DLMP-based under demand uncertainty," Applied Energy, Elsevier, vol. 330(PB).

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