EV Profile Capture

Dataset · Fri Jan 30 00:00:00 EST 2026

DOI:https://doi.org/10.15483/2574505· OSTI ID:2574505

Thurston, Sam ^[1]; Wells, Landon ^[1]; Vartak, Payas ^[1]

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1. Argonne National Laboratory

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.

• Research Organization: National Renewable Energy Laboratory; Pacific Northwest National Laboratory; Idaho National Laboratory
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office (EE-3V)
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 2574505
• Country of Publication: United States
• Language: English

Related Subjects

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