## 1 Introduction
[PERSON] and [PERSON] [19] examined the impact of various environmental conditions, including parking and driving conditions, on the feasibility of solar EVs. The International Energy Agency (IEA) report [20] identified several factors that reduce the efficiency of solar EV systems, including shading losses (\(-\)30%), maximum power point tracking losses (\(-\)5%), DC/DC conversion losses (\(-\)5%), and DC charging/discharging losses (\(-\)2%). One of the most active areas of research is EV charging stations, with many studies analyzing the considerations, optimal locations, and technical and economic implications of their introduction [21; 22; 23; 24]. Several studies have investigated parking space for solar EVs, including optimal installation and operation planning [25; 26] and the prediction of the charging rate of solar EVs during parking time by considering the insolation [27; 28]. To identify shaded areas that reduce solar EV power generation, a street view image was utilized to derive the hourly shaded area on a road [29], and a shading matrix was created by comparing modeling and field measurements to calculate the hourly percentage of shaded area for a given location [30]. In addition to the technical aspects of solar EVs, research has also been conducted on the policy side. [PERSON] and [PERSON] [31] observed that France is evaluating various innovation policies to promote solar mobility by 2030, aiming to achieve environmental, economic, and social goals. They found that a policy combining research and development subsidies and a carbon tax would be most effective, and public acceptance is crucial for the widespread adoption of solar mobility technology. Recently, several studies have evaluated the PV potential of solar vehicles including buses, trains, and cars. A model to predict the power production of a solar bus with a solar roof has been developed and validated via in situ experiments [32; 33]. An algorithm for predicting the PV potential of a solar train has been proposed, assuming that the modules are attached to the roof of the train and reflect spatially and temporally varying insolation and shadow effects during operation [34]. [PERSON] et al. [11] evaluated the potential of an EV with PV modules on all four sides of the vehicle (roof, rear window, and doors on both sides), depending on the driving route and travel time. By considering the tilt and orientation angles of each PV module attached to the vehicle and the tilt and orientation angles of the road along the driving route, the sunlight collection efficiency and potential of each EV module were evaluated. However, the above-mentioned studies are limited in that they focused on developing a model to calculate the power generation of solar mobility in a specific environment without discussing its practical utility. To expand the awareness of the utility of solar EVs, their potential should be evaluated by considering the operation methods of users. To date, no studies have been conducted to estimate the PV potential of commuters using solar EVs based on their vehicle operation methods. The objective of this study is to estimate the PV potential of a solar-roofed EV while a commuter is driving on an expressway. To fulfill the addressed goals, the study built a database of spatiotemporal weather characteristics in a geographic information system (GIS) environment and presented the potential for each driving section and driving time of the EV. Under the assumption of a commuting scenario for office workers in the study area, the study predicted battery charging and consumption during driving and parking. This study differs from previous studies in that it considers the operation of solar EVs by commuters and discusses the utility and feasibility of solar EVs as a battery-charging supplement.