Torgue and flux ripple mitigation technique using multi-level inverter for sequential model predictive controlled induction motor

Abstract

The control of electric motors presents a fascinating topic in the field of electrical engineering. Three-phase induction motors are extensively employed in industrial applications, because of their durability and cost-effectiveness. Hence, induction motor control research remains a major priority in electrical drive technology. Field-oriented control (FOC) and direct torque control (DTC) are the most common control methods for industrial applications up to now. Recently developed microcontroller processing capabilities have enabled novel control technology like model predictive control (MPC). High-performance drive systems could benefit from this new control method. One of MPC approach, referred to as finite control set-model predictive control (FCS-MPC), focuses on reducing a single cost function. This is achieved by adjusting a weighting factor to prioritize either torque or flux error reduction. However, the primary drawbacks of the standard FCS-MPC lie in determining these weighting factors and the variable switching frequency, which greatly varies based on the operational conditions. A control approach that eliminated the weighing factor was proposed. The proposed sequential model predictive control (SMPC) method is applied to a 3-phase induction motor operated by a 5-level CHB inverter. Simulation results matched theoretical analysis. Results demonstrated that stator flux and torque are independently controlled without weighting factor, and low harmonic distortion levels.