Unified Optimal Control Method for SynRM in Full-Speed Region Considering Magnetic Saturation

This article proposes a novel unified optimal control method (UOCM) for synchronous reluctance motor (SynRM) considering magnetic saturation. The conventional methods require operating case classification based on torque and speed commands, which is complex and computationally intensive. Moreover, the conventional methods only obtain the local optimal current reference in the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) cases, even though the parameter variations due to magnetic saturation are considered. This article proposes a unified optimization criterion for different operating cases to avoid case classification. The proposed criterion is essentially an optimization problem on the torque curve, thus ensuring the ability to obtain the global optimal current reference even when the motor is deeply saturated. A finite current angle set-based search method (FCAS-SM) is proposed to determine the optimal current reference online, which is equipped with offline precomputed lookup tables (LUTs) to reduce the computational effort. Moreover, the proposed method ensures that the obtained current references are always attainable by dynamically limiting the torque command through a simple integral controller. Experiments are carried out on a 3-kW SynRM platform to verify the performance of the proposed method in full-speed and torque regions.

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Publication Details

Journal
IEEE Journal of Emerging and Selected Topics in Power Electronics
Published
2024-11-25
DOI
https://doi.org/10.1109/jestpe.2024.3505297
Citations
5
Primary Topic
Magnetic Bearings and Levitation Dynamics
Type
article
Field-Weighted Citation Impact
1.64
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article

Unified Optimal Control Method for SynRM in Full-Speed Region Considering Magnetic Saturation

Guijie Yang, Jianyong Su, Kaiwen Tan, Guodong Sun et al.
5 citations
IEEE Journal of Emerging and Selected Topics in Power Electronics
Magnetic Bearings and Levitation Dynamics
1.64
article

Unified Optimal Control Method for SynRM in Full-Speed Region Considering Magnetic Saturation

Guijie Yang, Jianyong Su, Kaiwen Tan, Guodong Sun, Bencheng Zhong
article en
5 citations

Abstract

This article proposes a novel unified optimal control method (UOCM) for synchronous reluctance motor (SynRM) considering magnetic saturation. The conventional methods require operating case classification based on torque and speed commands, which is complex and computationally intensive. Moreover, the conventional methods only obtain the local optimal current reference in the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) cases, even though the parameter variations due to magnetic saturation are considered. This article proposes a unified optimization criterion for different operating cases to avoid case classification. The proposed criterion is essentially an optimization problem on the torque curve, thus ensuring the ability to obtain the global optimal current reference even when the motor is deeply saturated. A finite current angle set-based search method (FCAS-SM) is proposed to determine the optimal current reference online, which is equipped with offline precomputed lookup tables (LUTs) to reduce the computational effort. Moreover, the proposed method ensures that the obtained current references are always attainable by dynamically limiting the torque command through a simple integral controller. Experiments are carried out on a 3-kW SynRM platform to verify the performance of the proposed method in full-speed and torque regions.

IEEE Journal of Emerging and Selected Topics in Power ElectronicsVol. 13(1)
Shenzhen Polytechnic University (CN), Harbin Institute of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 15%
Magnetic Bearings and Levitation Dynamics
1.64
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Unified Optimal Control Method for SynRM in Full-Speed Region Considering Magnetic Saturation — Guijie Yang, Jianyong Su, et al. · IEEE Journal of Emerging and Selected Topics in Power Electronics (2024) | TGRS Research Map | TGRS