Low-complexity model predictive control for series-winding PMSM with extended voltage vectors

Hu, Jinde, Fu, Zhaoyang, Xu, Rongwei, Jin, Tian, Feng, Jenny and Wang, Sheng ORCID: https://orcid.org/0000-0002-2258-2633 2025. Low-complexity model predictive control for series-winding PMSM with extended voltage vectors. Electronics 14 (1) , 127. 10.3390/electronics14010127

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Abstract

This paper proposes a low-complexity model predictive current control (MPCC) strategy based on extended voltage vectors to enhance the computational efficiency and steady-state performance of three-phase series-winding permanent magnet synchronous motors (TPSW-PMSMs). Compared to conventional MPCC methods, this approach increases the number of candidate voltage vectors in the alpha–beta plane from 8 to 38, thereby achieving better steady-state performance. Specifically, the proposed method reduces the total harmonic distortion (THD) by 59%. To improve computational efficiency, a two-stage filtering strategy is employed, significantly reducing the computational burden. The number of voltage vectors traversed in one control period is reduced from 38 to a maximum of 4, achieving an 89% reduction in traversals. Additionally, to mitigate the impact of zero-sequence currents, zero-sequence current suppression is implemented within the control system for effective compensation. By combining low computational complexity, reliable steady-state performance, and real-time control capabilities, this strategy provides an efficient solution for TPSW-PMSM systems. Simulation results validate the effectiveness of the proposed method.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Start Date: 2024-12-31
Publisher:	MDPI
Date of First Compliant Deposit:	15 January 2025
Date of Acceptance:	30 December 2024
Last Modified:	15 Jan 2025 10:45
URI:	https://orca.cardiff.ac.uk/id/eprint/175289

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