基于多项式磁饱和模型及EKF的感应电机磁链观测

doi:10.19595/j.cnki.1000-6753.tces.170096

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Abstract Rotor flux is an important parameter in vector control of induction motor. The flux is usually estimated from measured three-phase current, which is often being influenced by noise. The accuracy of observer is related with motor parameters. If the flux level varies with motor working points, the nonlinear magnetic saturation effect will cause variation of mutual inductance. Then, the amplitude and position of rotor flux will deviate from real value, deteriorating the control performance. In this paper, observer algorithm for state estimation and parameter identification, based on extended Kalman Filter (EKF) and forth-order polynomial magnetic saturation model, is proposed. The stator current works as feedback, to correct the predicted value from induction motor model. The simulation and experimental results show the effectiveness of the proposed algorithm in reducing the influence of magnetic nonlinear effect on control system.

Key words： Polynomial magnetic saturation model extended Kalmanfilter flux observer parameter identification

Received: 22 January 2017 Published: 10 November 2017

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TM343

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	LiuLu
	WangXiaonian
	Du Xudong

Cite this article:

LiuLu,WangXiaonian,Du Xudong. Flux Observer of Induction Motor Based on Polynomial Magnetic Saturation Model and EKF Algorithm[J]. Transactions of China Electrotechnical Society, 2017, 32(21): 77-86.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.170096 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I21/77

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