Abstract
In a motor control system, the parameters tuning of speed and position controller depend on the value of the moment of inertia. A new moment of inertia identification scheme for permanent magnet motor system was proposed in this paper. This is an extension of the existing acceleration deceleration methods, which solves the large moment of inertia identification error caused by variable angular acceleration, large calculation error of inertia torque, and large measurement noise in the acceleration process. Based on the fact that the angular acceleration is not constant and the sampling signal is noisy, the integral chain differentiator was used to calculate the instantaneous angular acceleration at any time and suppress the sampling signal noise at the same time. The error function with instantaneous angular acceleration and inertia torque as parameters was designed to estimate the moment of inertia. In order to calculate the inertia torque accurately, viscous friction torque was considered in the calculation of inertia torque, and Kalman filter was used to estimate the total load torque to solve the problem of under rank of motor motion equation. Simulation and experimental results showed that the proposed method could effectively identify the moment of inertia in both noisy and noiseless environments.
Highlights
Permanent magnet synchronous motor (PMSM) has been widely used in various industrial applications because of its high power density, high efficiency, and small size.To improve the performance of the PMSM control system, it is necessary to tune the parameters of the controller with the value of the moment of inertia
The error analysis of the existing acceleration deceleration moment of the inertia identification method was carried out. It showed that the error of the moment of inertia came from the measurement noise, inaccurate calculation of the instantaneous angular acceleration, and the corresponding moment of inertia torque in the existing identification method
In light of the shortcomings of the existing methods and the influence of sampling noise on the identification results in the experimental process, the inertial torque calculation, instantaneous angular acceleration calculation, and sampling noise suppression were considered in this paper
Summary
To improve the performance of the PMSM control system, it is necessary to tune the parameters of the controller with the value of the moment of inertia. Due to the under rank of the motion equation, the identification of the moment of inertia depends on the value of the total load torque. In order to improve the identification accuracy, [2] applied the fixed-order empirical frequency-domain optimal parameter estimation method and Gopinath method to identify the moment of inertia and total load torque respectively, but the calculation burden of this method is large. In [3], the disturbance observer was used to estimate the disturbance torque and the estimated value was applied to the moment of inertia identification This method has good performance while it has a long convergence time. The first is to use one parameter identification algorithm to identify both the moment of inertia and the total load torque [5,6,7], but this method increases the complexity of the algorithm
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