Characterizing Radiated Electromagnetic Interference from a Power Converter for Improved Electromagnetic Compatibility

This paper investigates electromagnetic interference (EMI) in power converters, which are critical components in modern electrical systems. The study introduces a novel machine learning-based approach for analyzing both electric and magnetic field emissions, aiming to improve EMI characterization. A key focus is placed on evaluating how the choice of power switching devices—specifically MOSFETs versus IGBTs—affects EMI profiles under varying operating conditions. Experimental results support the proposed methodology, offering valuable insights into optimal switch selection for EMI reduction. This work provides a practical framework for designers and engineers to enhance regulatory compliance and minimize interference in electronic systems. Although not centered on environmental aspects, the reduction of EMI indirectly supports energy efficiency and contributes to more sustainable power conversion practices.