NEW PERSPECTIVES ON THE USE OF ASYNCHRONOUS MOTORS WITH A PHASE ROTOR BASED ON THE DOUBLE-FED INDUCTION MACHINE SCHEME
DOI:
https://doi.org/10.32782/3041-2080/2025-3-14Keywords:
asynchronous motors, phase rotor, double-fed induction machines, wind energy, mining industry, control algorithms, energy efficiencyAbstract
The article investigates new perspectives on the use of asynchronous motors with a phase rotor based on the double-fed induction machine (DFIM) scheme, which is one of the most versatile solutions for systems with adjustable electric drives. The relevance of the study is driven by the need to enhance energy efficiency, operational stability, and adaptability to changing operating conditions in industries such as wind energy, mining, and transportation.The study analyzes existing systems and identifies their main drawbacks, including sensitivity to network parameter changes and control complexity. The applied mathematical models account for effects in rotor windings and stator currents. Simulations were conducted to analyze the system’s performance under various load conditions.Proposed control algorithms ensure stable motor operation under dynamic load changes and minimize energy losses. The results of mathematical modeling confirm the effectiveness of the developed approaches, particularly in improving stability compared to traditional methods.The practical significance of the work lies in the potential implementation of the proposed solutions in wind energy and industrial systems, where high efficiency and reliability are critical. The findings contribute to the development of DFIM control systems and expand their application areas.
References
Gasmi H., Benbouhenni H., Colak I., Tafticht T., Bizon N. Using the proportional dual integral strategy to improve the characteristics of the indirect field-oriented control of DFIG-based wind turbine systems. e-Prime – Advances in Electrical Engineering, Electronics and Energy. 2024. Vol. 9. P. 100749. DOI: https://doi.org/10.1016/j.prime.2024.100749
Peresada S., Tilli A., Tonielli A. Power control of a doubly fed induction machine via output feedback. Control Engineering Practice. 2004. Vol. 12. Issue 1. P. 41–57. DOI: https://doi.org/10.1016/S0967-0661(02)00285-X
Xu L., Cheng W. Torque and reactive power control of a doubly fed induction machine by positionsensorless scheme. IEEE Transactions on Industry Applications. 1995. Vol. 31. No. 3. P. 636–642. DOI: https://doi.org/10.1109/28.382126
Moussaoui A., Ben Attous D., Benbouhenni H., Bekakra Y., Nedjadi B., Elbarbary Z. M. S. Enhanceddirect torque control based on intelligent approach for doubly-fed induction machine fed by three-level inverter. Heliyon. 2024. Vol. 10. Issue 21. DOI: https://doi.org/10.1016/j.heliyon.2024.e39738
Chantoufi A., Derouich A., El Ouanjli N., Mahfoud S., El Idrissi A. Improved direct torque control of doubly fed induction motor in electric vehicles using fuzzy logic controllers. e-Prime – Advances in Electrical Engineering, Electronics and Energy. 2025. Vol. 11. P. 100882. DOI: https://doi.org/10.1016/j.prime.2024.100882
Saihi L., Berbaoui B., Ferroudji F., Roummani K., Koussa K. Implementing an advanced neural in the integral sliding mode first order controller for wind turbine chains with DFIG. 2024 4th International Conference on Embedded & Distributed Systems (EDiS). BECHAR, Algeria, 2024. P. 325–329. DOI: https://doi.org/10.1109/EDiS63605.2024.10783214
Kadi S., Benbouhenn H., Hamdan I., Abdelkarim E. An advanced backstepping control scheme via active and reactive powers for DFIM-based on variable-speed turbine energy. Sohag Engineering Journal. 2024. ISSN 2735-5888. EISSN 2735-5896. DOI: https://doi.org/10.21608/sej.2024.338390.1071
Reigosa D. D., Guerrero J. M., Diez A. B., Briz F. Rotor temperature estimation in doubly-fed induction machines using rotating high-frequency signal injection. IEEE Transactions on Industry Applications. 2017. Vol. 53. No. 4. P. 3652–3662. DOI: https://doi.org/10.1109/TIA.2017.2684742
Madeswaran A., Bisht D., Yuvaraj S., Reedy M.U., Al-Attabi K., Dhablia A. AI-controlled wind turbine systems: Integrating IoT and machine learning for smart grids. E3S Web of Conferences. 2024. Vol. 540. P. 03008. DOI: https://doi.org/10.1051/e3sconf/202454003008
Liu Z., Zou L., Liu X. D., Pang S. Construction and testing of detailed simulation examples for wind turbine generator units. 2024 IEEE 7th International Electrical and Energy Conference (CIEEC). Harbin, China, 2024. P. 915–920. DOI: https://doi.org/10.1109/CIEEC60922.2024.10583822.
Клюєв О. В., Садовой О. В., Сохіна Ю. В. Системи керування асинхронними вентильними каскадами : монографія / Дніпр. держ. техн. ун-т (ДДТУ). Кам’янське: ДДТУ, 2018. 293 с.