Optimization of Power Electronics using Artificial Intelligence and Machine Learning Techniques

This project will propose new power electronics converter optimization techniques based on artificial intelligence and machine learning. The main aim is to investigate the use of artificial intelligence and machine learning techniques for the holistic multi-objective optimization of power electronics, with a focus on magnetic components' design, converter topology, thermal management, and cost. To validate the developed techniques, hardware prototypes will be designed and suitable benchmarking will be done against other established optimisation methods.

The work will begin with an extensive analysis, simulation, and modelling phase. Once successful solutions are identified, several case studies will be conducted. Finally, laboratory-based testing will begin to allow practical validation of ideas followed by implementation of the prototype test hardware.

The project is partially funded by CSA Catapult.