Search for: All records

Research on public charging station (PCS) selection has accumulated a large variety of variables that have been shown to affect charging behavior. We offer a human-centered framework to classify and integrate variables that have been described in the literature. Different from previous overviews, the framework focuses on the cognitive decision-making processes that are employed by human deciders. Every charging event includes a human decision that involves three dimensions: where to charge the vehicle (location), when to charge the vehicle (time), and for how long the vehicle is being charged (duration). The framework provides an overview of variables that have been studied in previous research and can be linked to these three dimensions. As a step to validate the framework, we asked 1,019 participants (including 667 owners of EVs or hybrid cars) how important each of 22 choice attributes would be for them when choosing a charging station. A factor analysis revealed the following six factors in descending order of perceived importance: costs, accessibility, time, past experience (self and other), amenities, and provider attributes. EV owners were also asked when and for how long they typically charge their vehicle. A factor analysis of the description of the time of charging confirmed a three-factor structure of range, finances, and habit. Results revealed systematic differences in the time and duration of charging between owners of hybrid cars and plug-in cars. Future research questions are discussed including the relevance of human-centered approaches for policies on charging station deployment and infrastructure planning. 

Abstract Unlike refueling at gas stations, charging an electric vehicle (EV) requires significantly more time, ranging from 20 minutes to over an hour, even with the fastest chargers. This prolonged charging duration introduces unique complexities to the fundamental understanding of public charging station (PCS) accessibility, raises questions about the ongoing relevance of spatial proximity for different population groups, and highlights the need to consider amenities near PCS that users can access along their daily routines. To account for these critical distinctions, we introduce visit-based accessibility, a metric that evaluates PCS availability relative to amenities frequented during urban routine activities. Leveraging data from over 28,000 PCSs, 5.2 million points of interest (POIs), and mobility patterns from more than 35 million cell phone users across 20 major U.S. metropolitan areas, we reveal a striking mismatch between PCS locations and the spatial proximity to and the daily needs of their intended users. While existing PCSs are spatially proximate to lower-income communities, our visit-based measure reveals significant disparities, as these communities' routine activities align significantly less with PCS locations. Furthermore, when considering dwell time at nearby amenities, higher-income communities exhibit better alignment of PCSs with routine activities and longer dwell times at nearby POIs, which are also the most extensively covered by existing PCSs. Finally, our analysis reveals that experienced income and racial segregation are likely the major impedance for accessing PCSs that are spatially adjacent, which highlights a hidden social barrier where greater divergence from typical social encounters near charging infrastructure is associated with lower visit rates to PCSs. These findings underscore the necessity for targeted strategies to ensure equitable access to charging infrastructure, addressing both spatial and functional disparities to promote sustainable and inclusive urban development. 

In this study, we raise the concern that current understandings of user perceptions and decision-making processes may jeopardize the sustainable development of charging infrastructure and wider EV adoption. This study addresses three main concerns: (1) most research focuses solely on battery electric vehicle users, neglecting plug-in hybrid (PHEV) and non-EV owners, thus failing to identify common preferences or transitional perceptions that could guide an inclusive development plan; (2) potential factors influencing charging station selection, such as the availability of nearby amenities and the role of information from social circles and user reviews, are often overlooked; and (3) used methods cannot reveal individual items' importance or uncover patterns between them as they often combine or transform the original items. To address these gaps, we conducted a survey experiment among 402 non-EV, PHEV and EV users and applied network analysis to capture their charging station selection decision-making processes. Our findings reveal that non-EV and PHEV users prioritize accessibility, whereas EV owners focus on the number of chargers. Furthermore, certain technical features, such as vehicle-to-grid capabilities, are commonly disregarded, while EV users place significant importance on engaging in amenities while charging. We also report an evolution of preferences, with users shifting their priorities on different types of information as they transition from non-EV and PHEV to EV ownership. Our results highlight the necessity for adaptive infrastructure strategies that consider the evolving preferences of different user groups to foster sustainable and equitable charging infrastructure development and broader adoption of EVs.