Super-linear Scaling Behavior for Electric Vehicle Chargers and Road Map to Addressing the Infrastructure Gap

TL;DR

This paper analyzes the growth of EV charging infrastructure, revealing super-linear scaling with population and providing a county-level roadmap to address infrastructure gaps for widespread EV adoption.

Contribution

It introduces a scaling analysis approach to estimate EV infrastructure needs and highlights the super-linear growth pattern, offering a new perspective on infrastructure planning.

Findings

EV infrastructure scales super-linearly with population

Current EV infrastructure is less mature than gasoline stations

Provides a county-level roadmap for infrastructure expansion

Abstract

Enabling widespread electric vehicle (EV) adoption requires substantial build-out of charging infrastructure in the coming decade. We formulate the charging infrastructure needs as a scaling analysis problem and use it to estimate the EV infrastructure needs of the US at a county-level resolution. Surprisingly, we find that the current EV infrastructure deployment scales super-linearly with population, deviating from the sub-linear scaling of gasoline stations and other infrastructure. We discuss how this demonstrates the infancy of EV station abundance compared to other mature transportation infrastructures. By considering the power delivery of existing gasoline stations, and appropriate EV efficiencies, we estimate the EV infrastructure gap at the county level, providing a road map for future EV infrastructure expansion. Our reliance on scaling analysis allows us to make a unique forecast in this domain.