Improved Duty Cycle Model‐Free Predictive Current Control Using Ultralocal Model with an Adaptive Scaling Factor for <scp>SPMSM</scp> Drives

This paper proposes an improved duty cycle model‐free predictive current control algorithm using ultralocal model (ULM) with an adaptive scaling factor for surface‐mounted permanent magnet synchronous motors (SPMSMs). First, the ULM of SPMSM is established, which uses an extended state observer (ESO) to obtain lumped disturbances in the system. Second, an easy‐implemented adaptive law without any machine parameter is devised to automatically update the scaling factor of ULM and ESO, thereby completely eliminating the sensitivity of conventional model predictive current control (MPCC) to motor parameter variation and system uncertainty. Third, 18 new virtual voltage vectors are constructed, which combine with the duty cycle control theory, significantly reducing the steady‐state fluctuations and total harmonic distortion of phase current. Simultaneously, a simple candidate voltage vector selection method is proposed, which abandons the cost function and enumeration process in conventional finite‐control‐set MPCC, consequently reducing the computational complexity greatly. Moreover, all simulation and experimental results have confirmed the feasibility and effectiveness of the proposed method. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.