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Parameter estimation for VSI-fed PMSM based on a dynamic PSO with learning strategies

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journal contribution
posted on 28.09.2016, 09:57 by Zhao-Hua Liu, Hua-Liang Wei, Qing-Chang Zhong, Kan Liu, Xiao-Shi Xiao, Liang-Hong Wu
A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key parameter estimation for permanent magnet synchronous machines (PMSMs), where the voltage-source-inverter (VSI) nonlinearities are taken into account in the parameter estimation model and can be estimated simultaneously with other machine parameters. In the DPSO-LS algorithm, a novel movement modification equation with variable exploration vector is designed to effectively update particles, enabling swarms to cover large areas of search space with large probability and thus the global search ability is enhanced. Moreover, a Gaussian-distribution based dynamic opposition-based learning (OBL) strategy is developed to help the pBest jump out local optima. The proposed DPSO-LS can significantly enhance the estimator model accuracy and dynamic performance. Finally, the proposed algorithm is applied to multiple parameter estimation including the VSI nonlinearities of a PMSM. The performance of DPSO-LS is compared with several existing PSO algorithms, and the comparison results show that the proposed parameters estimation method has better performance in tracking the variation of machine parameters effectively and estimating the VSI nonlinearities under different operation conditions.

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant (51374107,61503134,51577057, 61573299, 61403134), the China Postdoctoral Science Foundation funded project under Grant (2013M540628, 2014T70767), and the Hunan Provincial Education Department outstanding youth project under Grant (15B087).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Power Electronics

Pages

1 - 1

Citation

LIU, Z.-H. ... et al, 2016. Parameter estimation for VSI-fed PMSM based on a dynamic PSO with learning strategies. IEEE Transactions on Power Electronics, 32 (4), pp. 3154-3165.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Acceptance date

11/05/2016

Publication date

2016-05-24

Notes

© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISSN

0885-8993

eISSN

1941-0107

Language

en