Salient pole type permanent magnet synchronous motor online parameter identification method

Abstract

The invention discloses a salient pole type permanent magnet synchronous motor online parameter identification method. By means of the method, alternating and direct-axis inductance and magnetic fluxlinkage in a system operation process can be decoupled out; furthermore, accurate identification is performed through a recursive least-squares method based on forgetting factors, accurate change of motor parameters is traced in real time, interaction among the parameters can be reduced in a process, a discreet value is close to a true value, effects of a plurality of interferences on the motor parameters in motor operation are reduced, the identification accuracy is improved to a great extent, and an algorithm is simple and convenient and easy to realize; meanwhile, existence of the forgetting factors can avoid the data saturation problem caused by too large data size; thus, the identification method is suitable for the situation that rotation speed and torque simultaneously change.

Description

technical field [0001] The invention relates to an on-line identification method for parameters of a permanent magnet synchronous motor, in particular to a technology for simultaneously realizing online identification of multiple parameters of a salient-pole permanent magnet synchronous motor based on a recursive least square method. Background technique [0002] The permanent magnet synchronous motor is a multivariable, strongly coupled nonlinear system. The change of the motor parameters has an important impact on the control effect. It changes with different working conditions at different times, and the coupling between the parameters can easily lead to the control effect not being achieved. expected. [0003] In order to improve the control performance of the system, it is necessary to decouple and identify the parameters of the motor to obtain accurate parameters. The existing multi-parameter online identification methods for permanent magnet synchronous motors are ge...

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Problems solved by technology

At present, the commonly used online parameter identification methods include least squares method, model reference adaptive method, extended Kalman filter method, etc., but these algorithms also have limitations such as large amount of calculation in application, and are easily affected by many disturbances in the operation of the motor.

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