Design of workplace and destination-based EV charging networks considering driver behavior, habits, and preferences

Many workplaces and other institutions are grappling with how to plan and deploy electric vehicle (EV) charging networks to support their employees and other constituents who drive EVs. We develop a novel approach for designing EV charging networks that is driver-centric: it estimates drivers' charging needs based on their driving and charging habits and determines the optimal number and type of chargers to install to meet those needs. Unlike prior literature, our framework establishes a unique individual profile for each driver based on their observed behaviors and habits. We demonstrate our approach at the University of California San Diego (UCSD) EV network of 439 charging ports using behavioral data derived from 800 EV drivers. We find that using unique driver profiles significantly increases expected network usage and size—in some cases requiring fivefold more workplace charging sessions and a threefold larger network compared to the same analysis based on regionally-averaged driver data. These increases are driven by drivers' tendency to recharge with high battery state-of-charge, which increases network size by 50 % alone and implies less value in using high-power chargers. An institution's goals for supporting drivers, which are important for equity, also significantly affect network size.