An enhanced model predictive control method with reduced computational load for three-level T-type inverter

Among three-level inverter topologies, the T-type configuration has gained prominence in low-voltage applications due to its favorable performance characteristics. Model predictive control has attracted considerable interest for such converters, offering the advantages of various control targets and a rapid dynamic response. However, the conventional approach is burdened by high computational load. In this study, the proposed strategy provides fewer evaluation times by reducing the number of rolling optimization by grouping candidate vectors. A novel sector-based distribution of candidate voltage vectors determined by the reference vector’s angular location is presented. By restricting the control cycle to the assessment of only seven candidate voltage vectors, the computational load is substantially reduced. Furthermore, the strategy effectively mitigates common-mode voltage, enhances current waveform quality, and decreases power dissipation in the switching devices without relying on a weighting factor. The proposed approach’s validity and effectiveness are demonstrated through simulation and experimental results applied to T-type inverter.