论文标题
电动汽车充电器和路线图的超级线性缩放行为，以解决基础设施差距
Super-linear Scaling Behavior for Electric Vehicle Chargers and Road Map to Addressing the Infrastructure Gap
论文作者
论文摘要
实现广泛的电动汽车（EV）采用需要在未来十年内实质性地构建基础设施。我们将充电基础设施需求作为扩展分析问题提出，并以县级解决方案来估算美国的EV基础设施需求。令人惊讶的是，我们发现当前的EV基础设施部署与人口超级线性相比，偏离了汽油站和其他基础设施的亚线性缩放。我们讨论与其他成熟的运输基础设施相比，这是如何证明EV站丰度的起步。通过考虑现有汽油站的电力传递以及适当的EV效率，我们估计了县级的EV基础设施差距，为未来的EV基础设施扩展提供了路线图。我们对扩展分析的依赖使我们能够在此领域中进行独特的预测。
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.
