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DOE OSTI · 3003107

A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data

Schmidt, Steven Knudsen [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000165590791)
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Abstract

With the expected increase in the number of electric vehicles (EVs) on the road in the coming years, it is important that analysis tools are capable of modeling and predicting the expected load on the power grid due to both individual EV charging sessions as well as large populations of vehicles. To do this accurately, the power profile of an EV charge session must be accurately modeled, including for scenarios where the temperature is above or below the ideal, and also take into account the nuances of manufacturer charging preferences. This paper introduces a method that utilizes the data in the Next-Gen Profile (NGP) data collection project to build a model of EV charging that takes into account the variations in charging power that occur due to off-nominal battery temperature and manufacturer preferences that limit power due to cold temperatures or high battery state-of-charge.

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24 - POWER TRANSMISSION AND DISTRIBUTION25 ENERGY STORAGE29 - ENERGY PLANNING, POLICY AND ECONOMY32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION33 ADVANCED PROPULSION SYSTEMSBatteryCharging ProfilesElectric VehiclesElectrical Grid

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Schmidt, Steven Knudsen [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000165590791). 2025-06-16. A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data. https://doi.org/10.2172/3003107

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