考虑逆变器非线性因素的表贴式永磁同步电机参数辨识

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Abstract Voltage-source inverter(VSI)nonlinearity will influence parameter identification accuracy of surface permanent magnet synchronous machines(SPMSM).This paper establishes a parameter identification model which is not affected by VSI nonlinearity,the process only need to transform stator voltage equations to eliminate the distorted voltage that caused by VSI nonlinearity.Besides,in order to improve convergence speed and reduce steady-state error of the identification results,the proposed method uses Adaline neural network method with a momentum item to identify motor parameters.Experimental results show that the proposed method can improve the identification precision of inductance,stator resistance and rotor flux linkage of the motor,and accelerate the convergence speed of identification results.

Key words： Surface permanent magnet synchronous machines(SPMSM) parameter identification voltage-source inverter nonlinearity Adaline neural network

Received: 19 March 2016 Published: 17 April 2017

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TM351

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	Shi Tingna
	Liu Hua
	Chen Wei
	Geng Qiang

Cite this article:

Shi Tingna,Liu Hua,Chen Wei等. Parameter Identification of Surface Permanent Magnet Synchronous Machines Considering Voltage-Source Inverter Nonlinearity[J]. Transactions of China Electrotechnical Society, 2017, 32(7): 77-83.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I7/77

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