Book Description
Electric vehicle (EV) market growth is critical to achieving sustainable development goals, governing aspirations to achieve full-scale electrification targets across the globe. Increasing EV sales have shifted the focus of researchers from EV adoption to new operational challenges such as the optimal deployment of charging stations and grid load management, which in turn also affects EV adoption. These challenges require an accurate characterization of EV user charging behavior, especially with evolving battery technology and driving ranges. This study critically reviews approaches and data sources used to elicit EV charging behavior and patterns from a demand-side perspective and investigates how supply-side studies on charging infrastructure deployment and management incorporate charging behavior. We observe a noticeable disconnect between both strands of the literature, as supply-side studies still rely on simplistic assumptions about charging behavior and focus on a handful of aspects in isolation. More specifically, several studies either consider personal EVs or ride-hailing services with only public fast-charging infrastructure while ignoring available home/work charging infrastructure. We recommend shifting from this silo approach to a system-level dynamic planning framework where future charging demand is forecasted by combining charging behavior models with the models to forecast travel demand and EV adoption, followed by an integration of demand information into the supply-side optimization. The framework can thus capture complex supply-demand interactions and inform the charging infrastructure planning policies, laying out a roadmap for emerging and mature EV markets.