Optimization of a Solar-Based Non-Isolated SIMO Boost DC-DC Converter for BLDC Motor Drives Using Portia Spider Algorithm

Abstract

This study presents an enhanced non-isolated single-input multi-output boost DC-DC converter applied in a solar-powered Brushless Direct Current (BLDC) motor drive, optimized using the Portia Spider Optimization Algorithm (PSOA). A major challenge in solar-based BLDC applications, particularly in electric vehicle drives, lies in the fluctuating and low direct current voltage output from photovoltaic panels. The proposed approach employs PSOA to tune a Tilted Integral Fractional Derivative with Filter plus Fractional Derivative (TIFDNFD) controller, thereby reducing settling time, overshoot, and improving voltage stability and conversion efficiency. Simulation results in MATLAB demonstrate that the proposed method achieves a rise time of 800 s, efficiency of 95%, and settling time of 2050 s—outperforming conventional approaches such as Cuckoo Search Optimization, Harris Hawks Optimization, and Whale Optimization Algorithm. The novelty of this work lies in integrating the biologically inspired PSOA for controller tuning in solar-powered BLDC motor drives. Recommendations for extending this work include testing under dynamic load conditions and integrating hybrid renewable sources for improved system reliability.