Improved Deadbeat Predictive Current Control to Enhance the Performance of the Drive System of Permanent Magnet Synchronous Motors

Abstract

Thanks to the features of fast dynamic response, excellent static tracking performance, and less computation efforts, the deadbeat predictive current control (DPCC) has been widely applied for permanent magnet synchronous motors (PMSMs) in various applications like electric vehicles, where high speed operation is often adopted for achieving high power density of the drive system. However, the DPCC is a model-parameter-sensitive control method, so inaccuracy of the PMSM model or model parameter mismatch will cause significant deviation in predicting the further behavior of the control variables. To address this issue, an improved DPCC with a novel predictive model of PMSM is proposed in this paper. The novel predictive model considers the core loss of the PMSM, which may be a significant part of the electromagnetic loss but neglected in the traditional DPCC. As a case study, the proposed DPCC is used to analyze the characteristics of a claw pole PMSM drive system. To validate the merits of the improved DPCC, the analysis results are compared with those of the traditional DPCC.