EV Profile Capture

Thurston, Sam; Wells, Landon; Vartak, Payas

doi:10.15483/2574505

Title: EV Profile Capture

Dataset
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Abstract

NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.

Authors:

Thurston, Sam; Wells, Landon; Vartak, Payas

Argonne National Laboratory

Publication Date:: Thu Dec 11 23:00:00 EST 2025

DOE Contract Number:: AC05-76RL01830

Research Org.:: National Renewable Energy Laboratory; Pacific Northwest National Laboratory; Idaho National Laboratory

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

Subject:: 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; electric vehicle charging load profiles; electric vehicle infrastructure planning; electric vehicles

OSTI Identifier:: 2574505

DOI:: https://doi.org/10.15483/2574505

Citation Formats


                    Thurston, Sam, Wells, Landon, and Vartak, Payas. EV Profile Capture.  United States: N. p., 2025. 
        Web.  doi:10.15483/2574505.

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                    Thurston, Sam, Wells, Landon, & Vartak, Payas. EV Profile Capture.  United States.  doi:https://doi.org/10.15483/2574505

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                    Thurston, Sam, Wells, Landon, and Vartak, Payas. 2025.  
"EV Profile Capture".  United States.  doi:https://doi.org/10.15483/2574505.  https://www.osti.gov/servlets/purl/2574505. Pub date:Thu Dec 11 23:00:00 EST 2025

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@article{osti_2574505,

  title        = {EV Profile Capture},

  author       = {Thurston, Sam and Wells, Landon and Vartak, Payas},

  abstractNote = {NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.},

  doi          = {10.15483/2574505},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Thu Dec 11 23:00:00 EST 2025},

  month        = {Thu Dec 11 23:00:00 EST 2025}

}

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DOI: https://doi.org/10.15483/2574505

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