An Improved Deadbeat Predictive Current Control with Online Parameter Identification for Surface-Mounted PMSMs

Journal article (2020)

Authors

Yu Yao Southeast University
Yunkai Huang Southeast University
Fei Peng Southeast University
J. Dong DC systems, Energy conversion & Storage - EEMCS
Hanqi Zhang Southeast University
Research Group
DC systems, Energy conversion & Storage (EEMCS) (TU Delft)
Copyright: © 2020 Yu Yao, Yunkai Huang, Fei Peng, J. Dong, Hanqi Zhang
DOI: https://doi.org/10.1109/TIE.2019.2960755
Parameters identification Disturbance observer DPCC SPMSM
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Published Date

2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

DC systems, Energy conversion & Storage

Abstract

In this article, an improved deadbeat predictive current control (DPCC) method with parameters identification for surface-mounted permanent magnet synchronous machines (SPMSMs) is proposed. With the proposed DPCC method, zero steady-state current error and deadbeat dynamic current response could be achieved, even with inaccurate initial motor parameters. On basis of the conventional DPCC method, a novel parameters identification for the stator resistance and inductance is developed, which is the main contribution of this article. The proposed parameters identification method works based on a reconstructed characteristic vector from the disturbance observer with current injection. Compared with traditional recursive-least-square methods, the proposed method can be implemented with greatly reduced computation burden. Additionally, since the design is established based on the fully discretized model, the effectiveness will be guaranteed on both low-frequency and high-frequency motors, which is a significant advantage of the proposed method.