An Integrated Boost Flyback Converter with EV Solar Charging Using Honey Badger Algorithm

The growing demand for environmentally friendly transportation highlights the importance of efficient and cost-effective Electric Vehicle (EV) charging systems powered by renewable energy. However, existing systems often suffer from low voltage gain, significant energy losses, and inadequate adaptation to fluctuating solar output. To address these challenges, this study proposes an Interleaved Boost Flyback Converter (IBFC) integrated into a solar EV charging system and optimized using the Honey Badger Algorithm (HBA). The proposed strategy aims to improve energy transfer efficiency from photovoltaic (PV) panels to EV batteries while minimizing operational costs. The IBFC architecture combines the advantages of boost and flyback converters to attain reduced energy losses and high voltage gain, while the HBA optimizes system operation for maximum power transfer. The proposed system is evaluated through simulations conducted in the MATLAB environment and compared to established strategies, such as Cuckoo Search Algorithm (CSA), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN). The findings indicate that the proposed strategy achieves a system efficiency of 99.9% while lowering energy costs to $0.16 per kWh, significantly outperforming existing solution. These findings demonstrate the system's potential to enhance the scalability and sustainability of solar-powered EV charging solutions.