PARAMETER IDENTIFICATION FOR PERMANENT MAGNET SYNCHRONOUS MOTOR BASED ON IMPROVED SOCIAL NETWORK SEARCH ALGORITHM

Tian De; Wu Xiaoxuan; Su Yi; Meng Huiwen

doi:10.19912/j.0254-0096.tynxb.2024-1852

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (4) : 604-611. DOI: 10.19912/j.0254-0096.tynxb.2024-1852

PARAMETER IDENTIFICATION FOR PERMANENT MAGNET SYNCHRONOUS MOTOR BASED ON IMPROVED SOCIAL NETWORK SEARCH ALGORITHM

Tian De, Wu Xiaoxuan, Su Yi, Meng Huiwen

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Abstract

Aiming at the shortcomings of traditional PMSM parameter identification methods, including slow identification speed, low precision, and proneness to fall into local optimality, a PMSM parameter identification approach based on the improved social network search （ISNS） algorithm in this paper is proposed. The ISNS algorithm incorporate the Tent chaotic initialization strategy, Levy flight strategy, golden sine strategy, and Gaussian mutation strategy in the fundamental SNS algorithm. With reference to the test function, the superiority of the proposed ISNS algorithm is validated.The simulation results show that compared with other optimization algorithms, the proposed PMSM parameter identification method based on ISNS algorithm is capable of obtaining more accurate, high-quality, and stable identification outcomes.The identification accuracy of stator resistance, d-axis inductance, q-axis inductance, and flux linkage of PMSM is 99.996%, 99.934%, 99.947% and 99.962%, respectively.

Key words

permanent magnet synchronous motor / parameter identification / social network search algorithm / improved social network search algorithm / online identification / wind power generation

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Tian De, Wu Xiaoxuan, Su Yi, Meng Huiwen. PARAMETER IDENTIFICATION FOR PERMANENT MAGNET SYNCHRONOUS MOTOR BASED ON IMPROVED SOCIAL NETWORK SEARCH ALGORITHM[J]. Acta Energiae Solaris Sinica. 2025, 46(4): 604-611 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1852

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