Crested Porcupine Optimizer for Intelligent Estimation of Current Ripple in Power Factor Correction Interleaved Boost Converters for Electric Vehicle Charging

Enhancing efficiency and power quality (PQ) in electric vehicle (EV) charging systems depends on power factor correction (PFC) interleaved boost converters (IBC). Traditional methods to assess current ripple produce misleading results which leads to decreased system performance and increased power losses. This research presents the Crested Porcupine Optimizer (CPO) as a novel solution for intelligent current ripple estimation in electric vehicle charging systems to overcome existing method limitations. The main goal consists of minimizing ripple formation while also reducing Total Harmonic Distortions (THD). The Proportional-Integral (PI) controller gain parameter optimization occurs through CPO processing which raises the converter performance standards. The proposed solution implemented on MATLAB while evaluated performance with Artificial Neural Network (ANN) and Bald Eagle Search Optimization (BESO) and Long Short-Term Memory (LSTM). Results show the CPO approach delivers THD at 0.99% which supports effective harmonic suppression to enhance PQ for EV chargers. The evaluation demonstrates that CPO successfully enhances the current ripple estimation capability to improve PFC IBC system operations in EV charging applications.