AI-DRIVEN SWITCHED CAPACITOR DUAL INPUT CONVERTER FOR SOLAR PV AND BATTERY ENERGY SYSTEMS

The rapid growth of distributed renewable energy systems has intensified the demand for compact, efficient, and intelligent power conversion architectures capable of integrating multiple energy sources. Switched-capacitor (SC) converter topologies have emerged as a promising solution due to their high power density, transformer less design, reduced electromagnetic interference, and inherent voltage boosting capability without relying on bulky magnetic components. However, conventional SC converters often face limitations in dynamic response, power-sharing coordination, and efficiency under fluctuating solar irradiance and varying battery states of charge. To address these challenges, this work proposes an AI-driven switched-capacitor dual-input converter (SC-DIC) designed for seamless integration of solar photovoltaic (PV) modules and battery energy storage systems in hybrid renewable power architectures. The proposed SC-DIC topology enables simultaneous processing of power from PV and battery sources, offering flexible operating modes such as PV-only operation, battery-assisted PV operation, battery charging, and standalone battery supply.

                Artificial intelligence techniques, including reinforcement learning, fuzzy logic control, and neural network-based predictive optimization, are employed to enhance real-time decision-making, regulate duty cycle modulation, and enable adaptive power flow under dynamic environmental and load conditions. The AI controller predicts optimal switching states, minimizes capacitor voltage ripple, enhances soft-charging behavior, and reduces stress on semiconductor devices. Furthermore, the intelligent supervisory layer ensures optimal maximum power point tracking (MPPT), efficient battery charge-discharge management, and improved transient performance under intermittent solar input. Simulation and analytical results demonstrate that the AI-driven SC-DIC achieves higher conversion efficiency, faster dynamic response, and improved stability compared with conventional dual-input converters and fixed-rule SC control methods. The system reduces switching losses, enhances voltage gain, and ensures balanced power sharing between PV and battery sources. With its compact design, intelligent control, and capability to integrate dual renewable sources, the proposed converter presents a scalable and robust solution for next-generation DC microgrids, solar home systems, EV charging stations, and distributed energy storage applications.