The rapid growth of electric vehicle (EV) adoption has intensified the demand for intelligent and user-independent charging technologies. Conventional plug-in charging systems are constrained by fixed infrastructure, manual cable handling, and limited adaptability in autonomous environments. This paper proposes a solar-assisted mobile robotic charging system that integrates wireless power transfer through Inductive Power Transfer (IPT), robotic navigation, and photovoltaic energy harvesting to provide an autonomous and contactless EV charging solution. The developed robotic platform is designed to autonomously navigate toward a parked EV, accurately align the transmitter coil with the onboard receiver coil, and initiate stable wireless charging with minimal human intervention. Solar energy captured using integrated photovoltaic panels is stored in an onboard battery system and utilized to power both the robotic drive mechanism and the charging operation, thereby reducing grid dependency and improving energy sustainability. An intelligent control framework coordinates robot mobility, coil alignment, and charging regulation to maintain efficient power transfer under varying operational conditions. Experimental validation confirms effective wireless energy transmission across the specified air gap, precise robotic positioning accuracy, and dependable solar-assisted operation under fluctuating irradiance levels. The proposed system demonstrates strong potential for deployment in smart parking infrastructures, autonomous transportation systems, and renewable-energy-based EV charging networks.

In this work, a solar-powered robotic wireless EV charging platform was successfully developed and validated through prototype-level experimentation. The proposed system integrates solar energy generation, energy storage, robotic mobility, and inductive power transfer to provide a flexible and contactless EV charging solution. Unlike conventional stationary charging stations, the robotic platform is capable of approaching the vehicle and positioning the charging coils automatically, thereby reducing user intervention and improving operational convenience. Experimental evaluation confirmed that the photovoltaic subsystem can effectively sustain daytime charging operations, while the wireless power transfer performance is significantly influenced by coil alignment accuracy. The reduction in charging efficiency under misalignment conditions emphasizes the need for precise positioning and intelligent alignment mechanisms. The overall results demonstrate the practicality and potential of combining renewable energy with autonomous mobile charging technologies for future smart transportation systems. Further advancements may focus on AI-based navigation, real-time alignment optimization, improved power transfer efficiency, and scalable high-power charging architectures for real-world EV applications.

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