Golden eagle optimized fractional-order PI controller design for a PFC SEPIC converter in EV charging

Area of Science:

• Electrical Engineering
• Control Systems
• Power Electronics

Background:

• Power factor correction (PFC) is crucial for electric vehicle (EV) chargers.
• Traditional PI controllers may not offer optimal performance for PFC converters.
• Fractional-order PI (FOPI) controllers offer enhanced control capabilities.

Purpose of the Study:

• To optimize the parameters of a fractional-order PI (FOPI) controller for a Single Ended Primary Inductor Converter (SEPIC) used in PFC applications.
• To enhance the performance of EV charger power converters using an advanced optimization algorithm.
• To compare the performance of the optimized FOPI controller with a conventional PI controller.

Main Methods:

• The study proposes using the Golden Eagle Optimization (GEO) algorithm for tuning FOPI controller parameters.
• The SEPIC converter model was derived using state-space averaging and reduced via the moment matching method.
• Integral Absolute Error (IAE) and Integral Square Error (ISE) were used as the objective functions for optimization.

Main Results:

• The GEO-tuned FOPI controller demonstrated superior performance compared to the conventional PI controller.
• Simulation results in MATLAB/SIMULINK showed improved settling time and a faster dynamic response.
• The proposed method effectively reduced inrush current and harmonic distortion, ensuring system stability.

Conclusions:

• The Golden Eagle Optimization effectively tunes FOPI controllers for SEPIC PFC converters.
• The optimized FOPI controller significantly enhances the performance and stability of electric vehicle charger power supplies.
• This approach offers a promising solution for improving the efficiency and reliability of EV charging systems.