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Quantum genetic algorithm-based parameter estimation of PMSM under variable speed control accounting for system identifiability and VSI nonlinearity

journal contribution
posted on 30.09.2016 by Kan Liu, Zi-Qiang Zhu
This paper proposes a multiparameter estimation scheme for permanent-magnet (PM) synchronous machines (PMSMs) under variable-speed control, of which the estimation model is full rank and has taken into account the estimation and compensation of voltage-source-inverter nonlinearity. During the proposed estimation, the PMSM will work under variable speed control, and two sets of machine data corresponding to two sets of different rotor speeds will be recorded and used for the calculation of the proposed estimation model. It shows that the proposed estimation model can be solved by using a conventional quantum genetic algorithm and can ensure the identifiability of all needed parameters owing to its inherent full rank feature. The performance test of the proposed estimation is then conducted on an interior PMSM, and it shows that parameters such as rotor PM flux linkage and winding resistance can be accurately estimated without the aid from nominal parameter values of PMSM. Therefore, the proposed method can be used for the condition monitoring of stator winding and rotor PMs.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Industrial Electronics

Volume

62

Issue

4

Pages

2363 - 2371

Citation

LIU, K. and ZHU, Z.Q., 2015. Quantum genetic algorithm-based parameter estimation of PMSM under variable speed control accounting for system identifiability and VSI nonlinearity. IEEE Transactions on Industrial Electronics, 62(4), pp. 2363-2371.

Publisher

© IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

This paper is in closed access.

ISSN

0278-0046

eISSN

1557-9948

Language

en

Exports