Easing range anxiety through user-specific patterns of transportation with simulations (ERUPTS) for electric vehicle transition

Many internal combustion engine (ICE) vehicle drivers would consider transitioning to an electric vehicle (EV), but they haven’t had practical experience driving an EV. Many current ICE and even EV drivers have what has been termed range anxiety, which is the concern that they will run out of charge before reaching a suitable place to recharge their vehicle. We utilize DIMO driving data at macro scale to demonstrate that the vast majority of driving would be satisfied by charging at individual drivers’ primary anchor locations (e.g. a home charging station) and the existing charging infrastructure by simulating EV ownership for current ICE drivers. 15 to 30% of drivers would never need to charge away from home, and 75 to 80% of all driving would be satisfied with only home charging. This simulation utilizes observed driver behavior in order to determine user-specific compatibility with different EV ownership scenarios and presents users with detailed and customized analyses as to how their operation of an EV would require visiting public chargers and charging capacity at their primary anchor. This information can be presented to drivers in order to demonstrate their objective compatibility with an EV as well as predict future needs for the EV charging network and the power grid. We utilize these simulations to discover locations where charging stations may not satisfy the needs of drivers as more ICE drivers transition to EVs. We further utilize current EV driving behavior to discover where the charging network is not meeting drivers’ needs. • We used DIMO driving data to simulate electric driving for gas vehicle drivers. • Simulations can determine how compatible driving is with an electric vehicle. • Simulations can estimate future spatial and temporal gaps in the charging network. • We used EV driving data to determine where charging stations are being avoided. • Charging at only primary anchors satisfies 75 to 80% of total driving needs.

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Publication Details

Journal
Renewable and Sustainable Energy Transition
Published
2025-05-02
DOI
https://doi.org/10.1016/j.rset.2025.100111
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Easing range anxiety through user-specific patterns of transportation with simulations (ERUPTS) for electric vehicle transition

Jeremy M. Lerner
Renewable and Sustainable Energy Transition
Electric Vehicles and Infrastructure
article

Easing range anxiety through user-specific patterns of transportation with simulations (ERUPTS) for electric vehicle transition

Jeremy M. Lerner
article en

Abstract

Many internal combustion engine (ICE) vehicle drivers would consider transitioning to an electric vehicle (EV), but they haven’t had practical experience driving an EV. Many current ICE and even EV drivers have what has been termed range anxiety, which is the concern that they will run out of charge before reaching a suitable place to recharge their vehicle. We utilize DIMO driving data at macro scale to demonstrate that the vast majority of driving would be satisfied by charging at individual drivers’ primary anchor locations (e.g. a home charging station) and the existing charging infrastructure by simulating EV ownership for current ICE drivers. 15 to 30% of drivers would never need to charge away from home, and 75 to 80% of all driving would be satisfied with only home charging. This simulation utilizes observed driver behavior in order to determine user-specific compatibility with different EV ownership scenarios and presents users with detailed and customized analyses as to how their operation of an EV would require visiting public chargers and charging capacity at their primary anchor. This information can be presented to drivers in order to demonstrate their objective compatibility with an EV as well as predict future needs for the EV charging network and the power grid. We utilize these simulations to discover locations where charging stations may not satisfy the needs of drivers as more ICE drivers transition to EVs. We further utilize current EV driving behavior to discover where the charging network is not meeting drivers’ needs. • We used DIMO driving data to simulate electric driving for gas vehicle drivers. • Simulations can determine how compatible driving is with an electric vehicle. • Simulations can estimate future spatial and temporal gaps in the charging network. • We used EV driving data to determine where charging stations are being avoided. • Charging at only primary anchors satisfies 75 to 80% of total driving needs.

Renewable and Sustainable Energy TransitionVol. 7
Providence Hospital (US)
Openalex Percentile: Top 93%
Electric Vehicles and Infrastructure
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