Work

Low-Complexity Model Predictive Control for Series-Winding PMSM with Extended Voltage Vectors

Year: 2024

Type: article

Abstract: A low-complexity model predictive current control (MPCC) strategy based on extended voltage vectors is proposed to improve computational efficiency and steady-state performance for three-phase series-winding permanent magnet synchronous motors (TPSW-PMSM). This method delivers excellent steady-state performance while substantially reducing the computational burden compared to conventional MPCC. First, a simplified sector selection method is employed to preselect the sector in which the reference voltage vector resides. Next, the reference voltage vector is used to filter out redundant candidate voltage vectors, thereby reducing computation and ensuring real-time control capabilities. Basic active voltage vectors are segmented and recombined according to their magnitudes, without complex duty cycle calculations to further streamline processing. To mitigate the impact of zero-sequence current, zero-sequence current suppression is employed for effective compensation within the control system. This strategy’s combination of reduced computational complexity, reliable steady-state performance, and real-time control establishes it as an efficient solution for TPSW-PMSM systems. Simulation results validate the effectiveness of the proposed method.

Source: Electronics

DOI: 10.3390/electronics14010127

Authors: Jinde Hu, Zhaoyang Fu, Rongwei Xu, Tian Jin, Jenny Feng, Sheng Wang

Institutions: Northwestern Polytechnical University, Cardiff University

Language: English

Topic: Multilevel Inverters and Converters

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,728