Predictive current control of asymmetrical six-phase induction motor without weighting factors

Abstract

Control of multi-phase machine in both healthy and post-fault operations has recently gained considerable interest. Finite control set model predictive control (FCS-MPC), in particular, has been proposed to drive multi-phase machines to avoid sophisticated pulse width modulation (PWM) methods. Nevertheless, FCS-MPC generally experiences some technical limitations. One of the widely reported challenges related to FCS-MPC is the weighting factor (WF) design, which is empirically designed and found to be an operating point dependent factor. Thus, assuming a constant WF can result in poor performance. In this paper, the prediction stage of FCS-MPC for asymmetrical six-phase (A6P) induction motor (IM) has been reformulated based on double dq (2dq) modeling approach. Unlike the reported vector space decomposing (VSD)-based FCS-MPC algorithms, the proposed approach results in four control variables (the stator sequence currents isα1,isβ1,isα2, and isβ2) which have the same priority. Thus, equal weighting factors could be used in the cost function, which will inherently minimize the effect of the circulating x-y current components. Performance comparison of the proposed method against VSD-based FCS-MPC is investigated. The theoretical findings are experimentally validated using a 1 kW prototype six-phase IM.