The model predictive current control (MPCC) method has the advantages of a simple structure and fast response. It has been regarded as one of the most effective methods for solving multiphase driving systems. However, mismatches in motor parameters will significantly degrade the MPCC method’s control performance. To solve this problem, a novel model-free predictive current control (MFPCC) method for a dual three-phase permanent magnet synchronous motor (DT-PMSM) based on an extended Kalman observer (EKO) is proposed in this paper. Firstly, the modulated virtual voltage vector (MVV) is synthesized to increase the modulation range and reduce the control error. Secondly, an ultra-local model with a parameter-interference term is established to improve the system’s robustness to parameter mismatches. By combining the duty-cycle calculation method without motor parameters, the current tracking accuracy has been significantly improved. Thirdly, the EKO was introduced to observe the nonlinear part to improve the accuracy of the ultra-local model. Fourthly, the triangle wave is proposed as the carrier wave, with the reference value updated at the half-sampling period, generating an asymmetric PWM waveform that accurately tracks the reference voltage vector and simplifies software implementation on a low-cost microprocessor. Finally, the validity of the proposed method was verified experimentally by comparing it with two existing methods.
Zhang et al. (Mon,) studied this question.