Reliability Analysis and Design of Fault-Tolerant Control Strategies for High-Power Wide-Bandgap (SiC/GaN) Semiconductor-Based Converters in HVDC and FACTS Systems

Abstract

High-power Silicon Carbide (SiC) converters are fundamental to modern energy systems, such as HVDC transmission, but their operational reliability remains a critical challenge, this research presents an integrated computational framework designed to holistically address both the reliability assessment and fault-tolerant operation of these systems, the methodology bridges the gap between micro-level material degradation and macro-level system dynamics through a sequential, two-phase approach implemented entirely in Python, the first phase develops a high-fidelity predictive reliability model based on Physics-of-Failure (PoF) principles, meticulously modeling the dominant failure mechanisms of Time-Dependent Dielectric Breakdown (TDDB) in the gate oxide and thermo-mechanical fatigue in bond wires, this is achieved by linking an electro-thermal simulation, which calculates device stresses from a given mission profile, with a Monte Carlo analysis to generate probabilistic lifetime predictions, the second phase focuses on designing a robust Fault-Tolerant Control (FTC) strategy for a Modular Multilevel Converter (MMC), this includes non-invasive algorithms for rapid fault diagnosis (open- and short-circuit), immediate isolation of faulty submodules, and a dynamic compensatory control algorithm that rebalances arm voltages and capacitor states to ensure seamless post-fault operation, the primary contribution of this work is the creation of a unified simulation tool that models the entire converter lifecycle, from gradual physical degradation to adaptive system response, providing crucial insights for designing more resilient and dependable power electronic systems.