基于神经网络的永磁同步电机多参数解耦在线辨识

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Abstract A parameters identification method for surface permanent magnet synchronous motors (SPMSMs) is put forward to eliminate the parameters coupling during the multi-parameter online identification in this paper. The parameters coupling are often caused by the rank-deficient of SPMSMs’ mathematical model. The proposed method based on neural network can identify the stator resistance, inductance and rotor flux by negative sequence d-axis current short-term injecting and minimum mean square algorithm. The impacts on identification accuracy due to the inverter voltage dropping and dead time can also be weakened by improving the network structure. The validity of the proposed method is proved by the experiment results.

Key words： Permanent magnet synchronous motor online identification motor parameters neural network

Received: 01 September 2014 Published: 10 April 2015

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TM351

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	Articles by authors
	Gu Xin
	Hu Sheng
	Shi Tingna
	Geng Qiang

Cite this article:

Gu Xin,Hu Sheng,Shi Tingna等. Muti-Parameter Decoupling Online Identification of Permanent Magnet Synchronous Motor Based on Neural Network[J]. Transactions of China Electrotechnical Society, 2015, 30(6): 114-121.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2015/V30/I6/114

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