scholarly journals Parameter identification of permanent magnet synchronous AC motor based on spectral method

2021 ◽  
Vol 2091 (1) ◽  
pp. 012007
Author(s):  
Yuhao Cong ◽  
Qingjiao Ji ◽  
Guang-Da Hu
Keyword(s):  
Parameter Identification ◽  
Permanent Magnet ◽  
Spectral Method ◽  
Measurement Data ◽  
Angular Speed ◽  
State Variables ◽  
Motor Speed ◽  
Multiple Parameters ◽  
Ac Motor ◽  
Relative Errors

Abstract This paper establishes a mathematical model with random terms for a permanent magnet synchronous AC motor, which is a nonlinear system using d - axis current, q - axis current and the rotor electric angular speed as state variables. The numerical solution obtained by the Euler-Maruyama method is used as the measurement data. Aiming at the parameter identification of the system, a step-by-step identification method based on the spectral method discretize the system first and then using the least squares is proposed. This method is used to identify multiple parameters of the motor in the same model. In step-by-step identification, firstly by fixing the motor speed, the system is transformed into a linear system, which is used to estimate the resistance, inductance and flux linkage. After that, the speed is not fixed, for the electrical parameters are known, we can identify damping and inertia by using mechanical equations. Finally, the experimental results show that the relative errors of the parameters identified by the proposed method are smaller, which shows the effectiveness of this method for multi-parameter identification.

scholarly journals Material parameter identification using finite elements with time-adaptive higher-order time integration and experimental full-field strain information

2021 ◽  
Author(s):  
Stefan Hartmann ◽  
Rose Rogin Gilbert
Keyword(s):  
Experimental Data ◽  
Finite Elements ◽  
Parameter Identification ◽  
Material Parameter ◽  
Measurement Data ◽  
Least Square ◽  
Image Correlation ◽  
Field Strain ◽  
Material Parameter Identification ◽  
Full Field

AbstractIn this article, we follow a thorough matrix presentation of material parameter identification using a least-square approach, where the model is given by non-linear finite elements, and the experimental data is provided by both force data as well as full-field strain measurement data based on digital image correlation. First, the rigorous concept of semi-discretization for the direct problem is chosen, where—in the first step—the spatial discretization yields a large system of differential-algebraic equation (DAE-system). This is solved using a time-adaptive, high-order, singly diagonally-implicit Runge–Kutta method. Second, to study the fully analytical versus fully numerical determination of the sensitivities, required in a gradient-based optimization scheme, the force determination using the Lagrange-multiplier method and the strain computation must be provided explicitly. The consideration of the strains is necessary to circumvent the influence of rigid body motions occurring in the experimental data. This is done by applying an external strain determination tool which is based on the nodal displacements of the finite element program. Third, we apply the concept of local identifiability on the entire parameter identification procedure and show its influence on the choice of the parameters of the rate-type constitutive model. As a test example, a finite strain viscoelasticity model and biaxial tensile tests applied to a rubber-like material are chosen.

Parameter identification for interior permanent-magnet synchronous motor

2007 ◽  
Author(s):  
Tomonobu Senjyu ◽  
Yohei Noguchi ◽  
Naomitsu Urasaki ◽  
Atsushi Yona ◽  
Hideomi Sekine
Keyword(s):  
Parameter Identification ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Interior Permanent Magnet
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