Optimal charging management and infrastructure planning for free-floating shared electric vehicles

Roni, Mohammad S.; Yi, Zonggen; Smart, John G.

doi:10.1016/j.trd.2019.09.021

Optimal charging management and infrastructure planning for free-floating shared electric vehicles

Journal Article · Fri Oct 04 00:00:00 EDT 2019 · Transportation Research. Part D, Transport and Environment

DOI:https://doi.org/10.1016/j.trd.2019.09.021· OSTI ID:1582572

^[1]; ^[1]; Smart, John G. ^[1]

Idaho National Lab. (INL), Idaho Falls, ID (United States)

Recently, major car-sharing service providers have begun to include electric vehicles (EVs) in free-floating car-sharing fleets. For these EVs, downtime due to charging, including time spent traveling to and waiting in queues at charging stations in a sparse charging infrastructure network, is a major barrier to sustainable operation. An intuitive solution to overcome this barrier is to increase the number of fast-charging stations in the fleet service area. This paper studies the relationship between fleet vehicle downtime and the number of charging stations by modeling the fleet operations of a major car-sharing service provider. An integer programming model is developed that jointly optimizes charging station allocation, in terms of the number and location of charging stations, and the assignment of EVs to charging stations. Case study results showed that fleet vehicle charging time comprises 72-75% of the total downtime spent on charging trips. This indicates that charging time, as opposed to travel time or waiting time, is the dominant component of total fleet downtime for charging. The study also shows that by adding 5 to 20 new charging stations reduces total fleet downtime and travel time during charging trips by 2-4% and 26-49%, respectively. Although adding new charging stations to the fleet service area reduces total charging trip travel time significantly, it does not reduce total downtime significantly. Results also show that if the EV battery state of the charge (SOC) threshold—below which a charging trip is initiated—is less than 18%, not all EVs in the car-sharing fleet can be charged using the existing direct current fast chargers (DCFCs) in the fleet’s service area. Furthermore, this implies that adequate charging infrastructure coverage is required to ensure that EVs of a given range can operate in the car-sharing fleet.

View Accepted Manuscript (DOE)

Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 1582572

Alternate ID(s):: OSTI ID: 1780171

Report Number(s):: INL/JOU--18-45617-Rev000

Journal Information:: Transportation Research. Part D, Transport and Environment, Journal Name: Transportation Research. Part D, Transport and Environment Journal Issue: C Vol. 76; ISSN 1361-9209

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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car sharing
charging infrastructure
electric vehicle
integer programming
optimization

Optimal charging management and infrastructure planning for free-floating shared electric vehicles

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