Dead-Time Compensation Using ADALINE for Reduced-Order Observer-Based Sensorless SynRM Drives

Liangnian Lv, Ziyuan Wang, Xinru Zhao, Rui Guo, Jinpeng Wang (), Gaolin Wang and Shulin Li
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Liangnian Lv: Goldwind Science & Technology Co., Ltd., Beijing 830063, China
Ziyuan Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Xinru Zhao: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Rui Guo: Goldwind Science & Technology Co., Ltd., Beijing 830063, China
Jinpeng Wang: Goldwind Science & Technology Co., Ltd., Beijing 830063, China
Gaolin Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Shulin Li: Goldwind Science & Technology Co., Ltd., Beijing 830063, China

Energies, 2024, vol. 17, issue 7, 1-13

Abstract: The inverter dead time effect is non-negligible for the control performance of sensorless synchronous reluctance motor (SynRM) drives at low speeds. In this paper, a reduced-order observer-based sensorless control method for SynRM drives combined with the adaptive linear neurons (ADALINE)-based dead-time compensation is proposed. The reduced-order observer-based sensorless control method is presented, for which is parameter tuning is easy. On this basis, the dead-time compensation strategy using ADALINE filters is proposed to reduce the voltage harmonics effect on the estimation performance of the reduced-order observer. With ADALINE filters, the sixth current harmonic can be successfully filtered out by compensating the voltage directly or fitting the current to compensate the voltage. In this way, the low-speed estimation performance of the reduced-order observer is improved. The effectiveness of the proposed method is verified on a 3 kW SynRM experimental platform.

Keywords: synchronous reluctance motor; adaptive linear neurons; dead-time compensation; reduced-order observer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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