Abstract
In this paper, a speed control system for a three-phase induction motor was modelled and designed within LabVIEW software environment. After structuring the dynamical model of the motor, a current controller was developed to stabilize the system and avoid a wind-up situation. Then, a speed controller was designed, using PID and Field Weakening techniques, to generate the reference current values. The field-weakening algorithm is used to achieve stability at speeds that are higher than the nominal one. An estimator is used to calculate the flux angle and the electro-mechanical speed of the motor. As a result, the system achieved the desired speed with good transient and steady state responses. In addition, the system proved to be robust when the torque load is applied in all cases.
Highlights
Three phase induction motors (IM), squirrel cage, are rugged, efficient, and cheap compared to other motor types
Due to the high cost and low efficiency of the IM speed control techniques, the use of the three-phase induction motor was limited to the applications that have constant speeds, such as driving fans and pumps
The idea behind the vector control method is to identify the stator currents of an IM as two orthogonal components that can be visualized with a vector, which gives the ability to deal with the IM as a separately excited two-phase DC machine
Summary
Three phase induction motors (IM), squirrel cage, are rugged, efficient, and cheap compared to other motor types. Because of this, they are widely used in industry for many applications. In order to simulate the system and test it, the motor was modelled in LabVIEW using the T-model and the mathematical equations in the stationary reference frame, αβ. The vector control method, with PI and PID controllers, is used after converting the stationary variables αβ into a rotating dq reference frame using the Park transform. The Park transformation needs the rotor flux angle as input. This angle is difficult to be measured, a current estimator was used to calculate it. The system’s simulation was tested on two different speeds (1400) [rpm], which is the nominal speed, and (2000) [rpm], with and without the torque load, where the system stability was evident
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