Robust Predictive Current Control of Hybrid-Excited Axial Flux-Switching PM Motor Based on Multiple-Resolution Parameter Identification

Hybrid-excited axial flux-switching permanent magnet (HE-AFSPM) motor drives are nowadays considered for various applications due to numerous advantages when compared with traditional permanent magent (PM) motor counterparts. For the HE-AFSPM motor, to enhance the steady-state performance and reduce the tuning effort and computational time of model predictive current control (MPCC), in this article, a robust predictive current control (RPCC) method with multiple-resolution parameter identification is proposed and investigated. Based on the gradient of current variation, the predictive model of the HE-AFSPM motor is constructed. On this basis, the recursive least squares method is introduced, and identification matrices and multiresolution coefficients are designed for different operating conditions to achieve online optimization of identification target and frequency. The proposed method is compared with the conventional adaptive MPCC, and the effectiveness of the RPCC is confirmed by the experimental results.