Model-Based Predictive Vibration Suppression Algorithm for Permanent Magnet Synchronous Motor

Sheng Ma (), Xueyan Hao, Bo Zhang and Guilin Zhao
Additional contact information
Sheng Ma: College of Computer Science and Technology, Shenyang Institute of Engineering, Shenyang 110136, China
Xueyan Hao: College of Computer Science and Technology, Shenyang Institute of Engineering, Shenyang 110136, China
Bo Zhang: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110136, China
Guilin Zhao: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110136, China

Energies, 2025, vol. 18, issue 16, 1-12

Abstract: As applications like electric vehicles, all-electric ships, and all-electric aircraft continue to evolve, Noise, Vibration, and Harshness (NVH) issues have garnered extensive attention. However, as the core of the power system, permanent magnet synchronous motors (PMSMs) still lack control algorithms that consider vibration problems. Therefore, this paper proposes a model-based predictive vibration suppression algorithm to suppress the PMSM vibration. Firstly, this paper explores the influence of armature currents on vibration by analyzing the vibration characteristics of PMSMs, and proposes a minimum vibration current model. On this basis, according to the torque conditions required for the stable operation of the motor, a model-based predictive vibration suppression algorithm is designed. Finally, the effectiveness of the proposed algorithm is verified through prototype experiments.

Keywords: model predictive algorithm; vibration; vibration suppression (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/16/4252/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/16/4252/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:16:p:4252-:d:1721541

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().