Higher performance enhancement of direct torque control by using artificial neural networks for doubly fed induction motor

• Published in: e-Prime 2024-06, Vol.8, p.100537, Article 100537
• Main Authors: Mahfoud, Said, Ouanjli, Najib El, Derouich, Aziz, Idrissi, Abderrahman El, Hilali, Abdelilah, Chetouani, Elmostafa
• Format: Article
• Language: English
• Subjects: Artificiel neural networks; Direct torque control; Doubly fed induction motor
• ISSN: 2772-6711; 2772-6711
• DOI: 10.1016/j.prime.2024.100537

•Numerical investigation of an industrial gas turbine lean premixed burner through a high-fidelity CFD approach.•Validation of the numerical setup through a direct comparison with experimental data.•Assessment of the flame shape prediction of two enhanced versions of the FGM and ATF combustion models.•Remarkable accuracy in predicting the flame topology exhibited by both models.•Assessment of both turbulent combustion models in supporting burner design phase. Recently Direct Torque Control is widely appreciated compared to other conventional control methods due to its numerous advantages, notably its speed and precision. However, despite its qualities, it often encounters torque ripples that limit its operational effectiveness. These variations can be attributed to the use of hysteresis comparators, leading to variable frequency operation and undesirable speed overshoots. To address these challenges and enhance overall motor control, this article introduces a new approach based on neural networks. Direct Torque Control method is specifically designed for Doubly Fed Induction Motors and utilizes an Artificial Neural Network. Unlike conventional methods, this approach eliminates the need for speed controllers, commutation tables, and hysteresis comparators, thus providing a more integrated and efficient solution. Simulations conducted in the Matlab/Simulink environment have demonstrated the significant advantages of this approach with a higher performance enhancement. Not only were torque ripples reduced, but speed overshoot was completely eliminated. Furthermore, significant reductions in Total Harmonic Distortion values of stator and rotor currents were achieved, indicating an overall improvement in system performance.