A Survey Study on Optimization of Solar Power Systems Used in Charging Electric Vehicles Based on Artificial Intelligence Techniques | ||||
| Journal of Basic and Environmental Sciences | ||||
| Volume 12, Issue 3, July 2025, Page 107-132 PDF (543.25 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jbes.2025.380575.1018 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
heba makhlouf mohamed  1; Mostafa AlTokiy2; Reda Hendy Juma3; Ayman Haggag4
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| 1Faculty of Technology and Eduction, Helwan University | ||||
| 2Faculty of Technology and Education, Helwan University | ||||
| 3Faculty of Education- Banha university | ||||
| 4, Faculty of Technology and Education, Helwan University | ||||
| Abstract | ||||
| This survey study investigates the current state of research on the optimization of solar power systems used in charging electric vehicles (EVs) through the application of artificial intelligence (AI) techniques. Despite significant advancements, a critical research gap remains: the lack of a comprehensive mathematical model designed to minimize the surface area of photovoltaic panels while ensuring sufficient energy to charge EV batteries. This survey aims to address this gap by reviewing existing optimization methods and their application to solar-powered EV charging systems. The primary research questions posed are: "Which AI-based optimization techniques are most effective in minimizing the solar panel surface area required for EV charging?" and "What are the key factors and constraints that need to be considered in developing such a mathematical model?" Key hypotheses include the potential superiority of certain metaheuristic algorithms over others in achieving these objectives. Findings are systematically presented in tables, comparing various algorithms and highlighting their respective strengths and limitations. This study sets the stage for future research focused on developing a precise mathematical model to optimize solar panel usage for EV charging | ||||
| Keywords | ||||
| Electrical Vehicles (EVs); Sizing panel; Metaheuristic Algorithms; battery storage | ||||
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