Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles

Ucer, Emin; Koyuncu, Isil; Kisacikoglu, Mithat C.; Yavuz, Mesut; Meintz, Andrew; Rames, Clement

doi:10.1109/TTE.2019.2897088

Title: Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles

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Abstract

The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading and customer service quality. Furthermore, the relationship between the initial investment decision on building certain number of ports and customer satisfaction should be quantified. This paper aims to analyze these aspects using one million vehicle days of travel data within the Columbus, OH, USA, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural - to quantify the effect of uncertain parameters on DCFC station loading and service quality. Additional simulations based on a homogeneous vehicle population are carried out, and closed-form equations are derived therefrom to estimate charging duration and waiting time in the queue. Optimization of DCFC station design is also addressed through the number and capacity of ports.

Authors:

Ucer, Emin ^[1]; Koyuncu, Isil ^[1]; Kisacikoglu, Mithat C. ^[1]; Yavuz, Mesut ^[1]; Meintz, Andrew ^[2]; Rames, Clement ^[2]

Univ. of Alabama, Tuscaloosa, AL (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:: Fri Feb 01 00:00:00 EST 2019

Research Org.:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

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

OSTI Identifier:: 1507289

Report Number(s):: NREL/JA-5400-73663
Journal ID: ISSN 2332-7782

Grant/Contract Number:: AC36-08GO28308

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Transportation Electrification (Online)

Additional Journal Information:: Journal Name: IEEE Transactions on Transportation Electrification (Online); Journal Volume: 5; Journal Issue: 1; Journal ID: ISSN 2332-7782

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 33 ADVANCED PROPULSION SYSTEMS; DC fast chargers; electric vehicles; modeling; optimization; queueing

Citation Formats


                    Ucer, Emin, Koyuncu, Isil, Kisacikoglu, Mithat C., Yavuz, Mesut, Meintz, Andrew, and Rames, Clement. Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles.  United States: N. p., 2019. 
Web.  doi:10.1109/TTE.2019.2897088.

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                    Ucer, Emin, Koyuncu, Isil, Kisacikoglu, Mithat C., Yavuz, Mesut, Meintz, Andrew, & Rames, Clement. Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles.  United States.  https://doi.org/10.1109/TTE.2019.2897088

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                    Ucer, Emin, Koyuncu, Isil, Kisacikoglu, Mithat C., Yavuz, Mesut, Meintz, Andrew, and Rames, Clement. Fri .  
"Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles".  United States.  https://doi.org/10.1109/TTE.2019.2897088.  https://www.osti.gov/servlets/purl/1507289.

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@article{osti_1507289,

  title        = {Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles},

  author       = {Ucer, Emin and Koyuncu, Isil and Kisacikoglu, Mithat C. and Yavuz, Mesut and Meintz, Andrew and Rames, Clement},

  abstractNote = {The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading and customer service quality. Furthermore, the relationship between the initial investment decision on building certain number of ports and customer satisfaction should be quantified. This paper aims to analyze these aspects using one million vehicle days of travel data within the Columbus, OH, USA, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural - to quantify the effect of uncertain parameters on DCFC station loading and service quality. Additional simulations based on a homogeneous vehicle population are carried out, and closed-form equations are derived therefrom to estimate charging duration and waiting time in the queue. Optimization of DCFC station design is also addressed through the number and capacity of ports.},

  doi          = {10.1109/TTE.2019.2897088},

  journal      = {IEEE Transactions on Transportation Electrification (Online)},

  number       = 1,

  volume       = 5,

  place        = {United States},

  year         = {Fri Feb 01 00:00:00 EST 2019},

  month        = {Fri Feb 01 00:00:00 EST 2019}

}

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