MTPA-Based Finite-Set Model Predictive Control Without Weighting Factors for Linear Induction Machine

Abstract

The efficiency of the linear induction machine (LIM) is considerably low due to the large air-gap length and the additional losses resulting from the end-effects. However, so far, a little concentration has been done to increase the efficiency of this kind of motor. Therefore, the main objectives of this article are to eliminate the weighting factor, reduce the calculation steps, and increase the efficiency of the LIM aiding with a proposed finite-set model predictive direct flux control (FS-MPDFC), depending upon the maximum thrust per ampere (MTPA) strategy. The proposed FS-MPDFC is only based on the primary flux-linkage with the help of a novel cost function that does not require any weighting factors in order to considerably reduce the calculation steps. Moreover, the proposed FS-MPDFC is better than the model predictive current control in reducing the calculation step and decreasing the dependence on the transformation matrix and the machine parameters. In order to illustrate the effectiveness of the proposed MTPA-based FS-MPDFC, a comparison between the FS-MPDFC, with and without MTPA, and the previously suggested control techniques is presented and discussed. Moreover, a test bench platform of two 3-kW arc induction machines is constructed to emulate the drive performance of the actual LIM. Comprehensive simulation and experiments have fully demonstrated that the proposed FS-MPDFC with MTPA has lower calculation step, lower thrust ripple by 7%, and lower primary flux-linkage ripple by 0.4% compared to those of the FS-MPDTC. Moreover, the efficiency-based FS-MPDFC with MTPA is increased by 4% compared to that of the FS-MPDFC without MTPA.