Bidirectional Converter for On-Board Battery Charging in Plug-In Hybrid Electric Vehicles Using Reptile Search Optimization (RSO)

A novel hybrid control strategy for a bidirectional DC-DC converter used in on-board battery charging systems of Plug-In Hybrid Electric Vehicles (PHEVs). The proposed method utilizes the Reptile Search Optimization (RSO) algorithm to enhance control performance by dynamically adjusting gate signals to manage charging and discharging modes efficiently. The hybrid control scheme integrates both rule-based logic and intelligent decision-making to ensure robust energy flow management between the battery and the vehicle’s DC bus. RSO is utilized to minimize tracking errors and optimize the switching pattern to improve charge efficiency, battery lifespan, and the overall system. The converter operates in buck mode during charging from the grid or renewable sources, and in boost mode during battery discharge to support vehicle load. Simulation results demonstrate the effectiveness of the proposed control technique in maintaining desired State of Charge (SOC) levels, reducing power losses, and ensuring seamless transition between operating modes. Comparative analysis against conventional PSO-based and rule-based controllers confirms the superiority of the RSO-based approach in terms of convergence speed and control accuracy. This research contributes to the development of more reliable and energy-efficient PHEV charging systems using advanced bio-inspired optimization techniques.