Campus Units

Civil, Construction and Environmental Engineering

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

4-2017

Journal or Book Title

Transportation Research Part C: Emerging Technologies

Volume

77

First Page

462

Last Page

477

DOI

10.1016/j.trc.2017.02.014

Abstract

This paper presents a data-driven optimization-based approach to allocate chargers for battery electric vehicle (BEV) taxis throughout a city with the objective of minimizing the infrastructure investment. To account for charging congestion, an M/M/x/s queueing model is adopted to estimate the probability of BEV taxis being charged at their dwell places. By means of regression and logarithmic transformation, the charger allocation problem is formulated as an integer linear program (ILP), which can be solved efficiently using Gurobi solver. The proposed method is applied using large-scale GPS trajectory data collected from the taxi fleet of Changsha, China. The key findings from the results include the following: (1) the dwell pattern of the taxi fleet determines the siting of charging stations; (2) by providing waiting spots, in addition to charging spots, the utilization of chargers increases and the number of required chargers at each site decreases; and (3) the tradeoff between installing more chargers versus providing more waiting spaces can be quantified by the cost ratio of chargers and parking spots.

Research Focus Area

Transportation Engineering

Comments

This is a manuscript of an article published as Yang, Jie, Jing Dong, and Liang Hu. "A data-driven optimization-based approach for siting and sizing of electric taxi charging stations." Transportation Research Part C: Emerging Technologies 77 (2017): 462-477. DOI: 10.1016/j.trc.2017.02.014. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Ltd.

Language

en

File Format

application/pdf

Published Version

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