Variable Sampling Frequency Model Predictive Torque Control for VSI-Fed IM Drives Without Current Sensors
Ze Li, Yuanbo Guo, Jinhui Xia, Haoyang Li, Xiaohua Zhang
Abstract
For the purpose of improving the reliability, reducing the cost, and stabilizing the switching frequency of induction motors (IMs), a variable sampling frequency model predictive torque control (VSF-MPTC) for two-level voltage source inverter (VSI)-fed IM drives without current sensors is proposed in this article. This method first predicts the stator currents and stator flux by discretizing the mathematical model of the IM and replaces the measured currents and estimated stator flux with one-step delay of the predictive currents and flux, and then adjusts the average switching frequency to a low and quasi-constant level by increasing or decreasing the equivalent sampling frequency. Tedious tuning of weighting factor of the switching frequency in conventional model predictive control can be avoided. Meanwhile, the proposed scheme takes a shorter computation time by dividing the predictive variable into a variable component and a fixed component, which makes it possible to further decrease the minimum sampling period. The experimental results for a 2.2-kW IM are presented to illustrate the effectiveness of the proposed scheme.