Enhanced Predictive Torque Control Strategy for Six-Phase Induction Machines: A Comparative Study

Model predictive control (MPC) emerges as a compelling control strategy, finding successful applications in multiphase induction machines (IMs). A notable characteristic of multiphase IMs is their intrinsic fault tolerance compared to three-phase IMs. However, multiphase machines also introduce additional degrees of freedom (x − y) voltages or currents (related to machine losses and do not contribute to torque generation), which are absent in their three-phase counterparts. In this context, MPC can integrate various constraints through a cost function to regulate the (x − y) components while potentially affecting flux and torque production. The predictive torque control (PTC) has recently been combined with virtual vectors to reduce (x − y) currents and improve performance. However, no studies have compared it with the classic PTC since it is a new approach. This paper compares classic PTC and PTC using virtual vectors (PTC-VV) for a six-phase IM regarding stator current, torque, and speed regulation. Therefore, through simulation and experimental studies, the effectiveness of each approach is highlighted. The results show that integrating virtual vectors in the PTC approach reduces (x − y) currents in multiphase IM while maintaining the fast dynamic response.