## 5 Discussion
### From Simulation to Real-World Application  
While this study used data and a couple of assumptions to assess the PV potential of solar EVs, there are factors that should be considered when applying the data in the real world. Therefore, the possible differences between simulation-based PV potential and real-world application were addressed along with their causes.  
Firstly, clouds and trees are two environmental factors away from the solar EV that can reduce the accuracy of the estimated PV potential of solar EV. In real-world scenarios, clouds and trees act as light obstructions that can shade the solar roof of the EV, thereby reducing power generation. However, accounting for these factors in simulations is often challenging. The location and size of clouds can be estimated from weather data and satellite imagery, but their real-time variability makes them difficult to incorporate accurately beyond short-term forecasts. Trees around the expressway, depending on their size and density, can be considered in input data. For instance, the distribution and height of forests can be integrated using vegetation data, but individual trees with low density pose challenges for precise shade modeling. Therefore, trees can be considered as an input factor for shading modeling depending on their density. However, in this study, the shading effects of clouds and trees were not included in the power generation prediction. Consequently, actual power generation may be lower than the simulation predictions when field verification is conducted.  
Secondly, soiling and bird droppings are the two environmental factors on the car reducing power generation efficiency in real-world applications. If these factors continue to occur, they can also cause damage (wear and tear) to the PV modules, resulting in further degradation. These are the same factors that reduce the efficiency of ground-mounted PV modules. If certain parts of a PV module are covered by soiling or bird droppings, those cells will not generate power, which can also affect the performance of the whole module. With cells connected in series, a problem with one cell can affect the power production of the entire circuit. Although the impact of soiling and dirt is acknowledged, quantifying their effects on EV solar roofs in terms of probability or magnitude remains challenging. However, if the driver checks, cleans, or maintains these events between trips, the reduction in power generation can be minimized.  
The third is the variability of power generation due to uncertainty in site weather. In this study, TMY data, which are representative of long-term weather characteristics, was used to evaluate the PV potential of solar EVs throughout the year. However, the uncertainty or variability of weather conditions is the biggest reason for prediction errors. Therefore, for short-term forecasts such as tomorrow or the day after tomorrow, this may be a way to reduce uncertainty by evaluating the power generation potential using short-term forecast data rather than TMY data.  
The fourth is the driving style of the commuter that can influence the PV potential of solar EVs in real-world conditions. Although autonomous vehicles or cruise control functions can maintain a constant speed, this study assumes that commuters are manually driving the vehicles, resulting in potential variations in driving speed depending on the route. Consequently, not all commuters exhibit the same driving style. The subjective driving habits of drivers are significant as they affect both power generation and fuel efficiency, as demonstrated in Figure 8. Further research on these factors is necessary.