Polynomial Estimation of Flux Linkage for Predictive Current Control in PMSM

This article presents an automatic parameter identification method based on ordinary least square (OLS) algorithm for deadbeat predictive current control (DPCC) to fulfill the purpose of high steady and dynamic performance in permanent magnet synchronous motor (PMSM) drives. Different from the conventional model, a novel model based on the polynomial estimation of flux linkage is constructed which takes the cross-saturation effects into account. First, the conventional mathematical model of PMSM and the proposed model are presented, respectively, and the inverter considering nonideal factors is also analyzed. Then the parameter identification method is investigated, in which the measurement procedure is delimited in advance and the automatic identification method is developed. Furthermore, a voltage reconstruction algorithm is applied to solve the inverter nonlinearities and the digital time-delay effect, so as to improve the accuracy of the identified parameters. Accordingly, a novel DPCC algorithm is presented based on the proposed model to achieve better performance. Finally, based on the concept and principles mentioned before, a detailed comparison of the DPCC based on the classical model considering the parameters’ variation and the modified model of the proposed method is carried out on a laboratory prototype.