Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles

Khalid Alfuwail; Ali Nasir; Md Shafiullah; Ayman Abdallah

Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles

Abstract

Advanced technologies like Ram Air Turbines (RATs) are being investigated because of the aviation industry's need for fuel-efficient and alternative renewable energy sources. In situations where power generation is necessary in the event of an emergency involving unmanned aerial vehicles (UAVs), RATs are essential. Optimising the RATs' performance—including power output and operational stability—under variable and unexpected wind conditions is the main obstacle, though. Conventional control techniques frequently don't adjust to these changing conditions. In order to monitor the ideal turbine rotation speed, a sliding mode control rule is developed in the proposed controller. This article emphasises the need of using a recurrent neural network (RNN) to identify unpredictable wind turbine dynamics. Control over maximum power extraction is then made possible by the development of an online update mechanism that provides real-time weight changes for the RNN. Simulation findings show that, even in the presence of significant nonlinearities and system uncertainties, the proposed controller performs 13 times better than a conventional control strategy in monitoring the ideal turbine rotation speed and obtaining the maximum wind output from RATs.

Keywords

Supporting Institution

KFUPM

Project Number

51

Ethical Statement

The authors affirm that this research complied with ethical standards and professional integrity. No human or animal subjects were involved in this study, and all data used were obtained from publicly available sources or generated through simulations. Proper citations and acknowledgments have been provided for all referenced work to ensure transparency and academic honesty. This manuscript is the original work of the authors and has not been published or submitted elsewhere for publication. No conflicts of interest, financial or otherwise, are associated with this research. The study adheres to the ethical guidelines and policies of the journal to which it is submitted. Additionally, all authors contributed significantly to the research and have approved the final manuscript for submission.

Thanks

IRC-SES

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Details

Primary Language

English

Subjects

Power Electronics, Renewable Energy Resources , Simulation, Modelling, and Programming of Mechatronics Systems

Journal Section

Conference Paper

Authors

Khalid Alfuwail ^*
0009-0002-4442-3454
Saudi Arabia

Ali Nasir This is me
0000-0002-7789-428X
Saudi Arabia

Md Shafiullah This is me
0000-0003-2282-5663
Saudi Arabia

Ayman Abdallah This is me
0000-0002-9365-7364
Saudi Arabia

Publication Date

March 31, 2025

Submission Date

February 5, 2025

Acceptance Date

March 29, 2025

Published in Issue

Year 2025 Volume: 9 Number: 1

IZ

https://izlik.org/JA79CL96EZ

Cite

RIS / Bibtex

APA

Alfuwail, K., Nasir, A., Shafiullah, M., & Abdallah, A. (2025). Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles. International Journal of Engineering Science and Application, 9(1), 1-9. https://izlik.org/JA79CL96EZ

AMA

1.Alfuwail K, Nasir A, Shafiullah M, Abdallah A. Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles. IJESA. 2025;9(1):1-9. https://izlik.org/JA79CL96EZ

Chicago

Alfuwail, Khalid, Ali Nasir, Md Shafiullah, and Ayman Abdallah. 2025. “Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles”. International Journal of Engineering Science and Application 9 (1): 1-9. https://izlik.org/JA79CL96EZ.

EndNote

Alfuwail K, Nasir A, Shafiullah M, Abdallah A (March 1, 2025) Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles. International Journal of Engineering Science and Application 9 1 1–9.

IEEE

[1]K. Alfuwail, A. Nasir, M. Shafiullah, and A. Abdallah, “Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles”, IJESA, vol. 9, no. 1, pp. 1–9, Mar. 2025, [Online]. Available: https://izlik.org/JA79CL96EZ

ISNAD

Alfuwail, Khalid - Nasir, Ali - Shafiullah, Md - Abdallah, Ayman. “Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles”. International Journal of Engineering Science and Application 9/1 (March 1, 2025): 1-9. https://izlik.org/JA79CL96EZ.

JAMA

1.Alfuwail K, Nasir A, Shafiullah M, Abdallah A. Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles. IJESA. 2025;9:1–9.

MLA

Alfuwail, Khalid, et al. “Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles”. International Journal of Engineering Science and Application, vol. 9, no. 1, Mar. 2025, pp. 1-9, https://izlik.org/JA79CL96EZ.

Vancouver

1.Khalid Alfuwail, Ali Nasir, Md Shafiullah, Ayman Abdallah. Hybrid Sliding Mode Control and RNN-Based Strategy for Maximizing Power Extraction in Small Wind Turbines for Electric Vehicles. IJESA [Internet]. 2025 Mar. 1;9(1):1-9. Available from: https://izlik.org/JA79CL96EZ