## 1 Introduction  
Global efforts to combat climate change have intensified recently, as it remains one and affiliations. of the world's most pressing issues. A key focus of these initiatives is the decarbonization of automobiles, with ongoing research on solar-powered electric vehicles (SEVs). One of the primary advantages of SEVs is their ability to charge while in motion and when parked, which reduces both the frequency and length of stops at charging stations [1]. In addition, SEVs can serve as emergency power sources during disasters. However, SEVs face several challenges, particularly regarding their power generation capacity. These challenges can be categorized into two main issues: a lack of stability and immediacy in both power generation and charging. Although gasoline-powered vehicles provide immediate energy on demand, solar power does not deliver energy as rapidly. It is also difficult to accurately predict solar power generation [2]. Furthermore, international standardization efforts grounded in fairness and scientific rigor are essential [3]. Even with flat panels, predicting solar power generation can be complex, as it is influenced by factors such as shading, weather conditions, module configuration, and cell size. Understanding these variables is crucial for optimizing energy output and ensuring reliable performance. Vehicle-mounted solar panels are curved, adding complexity owing to self-shadowing, where sections of the panel cast shade on other sections [4]. The curve shape also affects the angular response, causing curve loss [5; 6]. It is necessary to consider that sunlight is divided into two components, direct and scattered, for the curved surface because the incident angles differ at each point on the curved surface [7]. As vehicles move, the vehicle-mounted solar panels are shaded by trees, buildings, and other objects around the road. The shadow partially covers the solar panel, causing partial shading loss [8]. In the case of parking, daily parking in the shade leads to a linear decrease in harvested energy [9]. Driving speed affects the operating temperature of vehicle-mounted solar panels [10], and changes in driving direction cause changes in the Sun direction, leading to a change in angular response [11]. In this context, the performance of vehicle-integrated photovoltaics (VIPVs) can be significantly affected by the environmental conditions and vehicle dynamics. The interaction of light with curved surfaces introduces challenges that differ from those encountered in traditional flat panel photovoltaics. The self-shadowing phenomenon, where parts of the panel shadow other sections, must be thoroughly understood to predict and optimize power generation. This issue becomes even more complex when considering the movement of the vehicle, as changes in orientation and speed alter the shading pattern continuously. Additionally, environmental factors such as the angle of the Sun, cloud cover, and temperature fluctuations can introduce variability in the solar irradiance. This study assesses incident light, which is a crucial factor in calculating power generation. It accounts for weather conditions and self-shadowing, offering practical insights for the design and implementation of VIPVs. Accurate predictions of power generation are essential to maximizing the benefits of SEVs, especially as they become more integrated into daily life. Furthermore, the optimal design and integration of photovoltaic systems in vehicles is vital for ensuring that these systems can meet the energy demands of electric vehicles while remaining cost-effective. Given these complexities, a detailed understanding of the incident light on VIPVs is necessary for effective power generation modeling. Previous studies have explored these challenges in various contexts [12; 13], but few have addressed the unique combination of factors at play in mobile systems such as SEVs.