AI-Enhanced EMC Digital Twin for Automotive WBG Converters

AI-Enhanced EMC Digital Twin for Automotive WBG Converters

This PhD studentship develops an AI-driven Digital Twin framework for Electromagnetic Compatibility (EMC) in Wide-Bandgap (SiC/GaN) power converters used in automotive applications. The project will develop predictive surrogate models using Physics-Informed Neural Networks (PINNs) and Gaussian Process Regression (GPR) to predict high-frequency conducted and radiated emissions, bridging virtual simulations with real-world physical compliance testing.

Research areas