Issue |
ITM Web Conf.
Volume 50, 2022
Fourth International Conference on Advances in Electrical and Computer Technologies 2022 (ICAECT 2022)
|
|
---|---|---|
Article Number | 03004 | |
Number of page(s) | 17 | |
Section | Electrical & Power Electronics | |
DOI | https://doi.org/10.1051/itmconf/20225003004 | |
Published online | 15 December 2022 |
Performance Enhancement of Induction Motor Based on Three-Level T-Type Inverter Using DTC-SVM
Middle Technical University, Baghdad, Iraq
* Corresponding Author: bcc0001@mtu.edu.iq
Induction motors (IM) that are driven using the conventional direct torque control algorithm (DTC) suffer from vital drawbacks which are high ripples in the torque and flux. These ripples result due to the use of a look-up table and hysteresis comparators which causes variable switching frequency. Moreover, the use of a traditional two-level inverter leads to the production of low-quality voltage and current. The work presented in this paper proposed a modified control system to overcome these drawbacks. The proposed control system is based on the use of the space vector modulation-based DTC algorithm (DTC-SVM) for driving three-phase IM via a three-level T-Type inverter. The conventional DTC-SVM algorithm has been modified to match the work of the proposed inverter. The modification process was based on the mapping of the standard DTC-SVM algorithm in the space vector of the three-level inverter. The conventional and the modified control systems are implemented using MATLAB/Simulink package. The comparison of the standard and the modified DTC-SVM has been performed by simulation. Simulation results showed the superiority of the proposed algorithm in terms of reducing ripple in torque and flux and improving the quality of current and voltage supplied to the motor.
Key words: Induction Motor / Direct Torque Control / DTC-SVM / 3-level T-type Inverter / 2-level inverter
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.