Finite Control Set Model Predictive Bridge Arm Fault Detection Strategy for T-Type Three-Level Inverter

To address the issues of complex algorithms and additional sensors in existing bridge arm open-circuit fault detection methods for inverter arms using current and voltage signals, this paper proposes a finite control set model predictive control fault detection method(FCS-MPCFDM) for T-type three-level grid-connected inverters. By designing a voltage vector estimation approach, the actual voltage vector corresponding to the inverter's switching states from the previous time step is obtained. This estimated vector is compared with the optimal voltage vector generated by FCSMPC, and combined with current direction analysis to enable fast fault detection and localization. The proposed method features a simple algorithm and eliminates the need for additional sensors. Simulation results confirm the effectiveness of this approach.