Treffer: Performance driven multi objective optimization of 2 MW integrated Pseudo Direct Drive permanent magnet synchronous wind generator.
Title:
Performance driven multi objective optimization of 2 MW integrated Pseudo Direct Drive permanent magnet synchronous wind generator.
Authors:
Abdeljalil D; Department of Electrical Engineering, National school of Engineering SFAX, LETI, University of SFAX, Sfax, Tunisia. dorra.abdeljalil@enis.tn., Krichen M; Department of Electrical Engineering, National school of Engineering SFAX, LETI, University of SFAX, Sfax, Tunisia., Benhalima N; Department of Electrical Engineering, National school of Engineering SFAX, LETI, University of SFAX, Sfax, Tunisia., Benhadj N; Department of Electrical Engineering, National school of Engineering SFAX, LETI, University of SFAX, Sfax, Tunisia., Neji R; Department of Electrical Engineering, National school of Engineering SFAX, LETI, University of SFAX, Sfax, Tunisia.
Source:
Scientific reports [Sci Rep] 2026 Feb 21. Date of Electronic Publication: 2026 Feb 21.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : Nature Publishing Group, copyright 2011-
References:
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Sethuraman, L. et K. L. Dykes, generatorse: a sizing tool for variable-speed wind turbine generators », National renewable energy laboratory (NREL), Golden, CO (United States), NREL/TP–5000–66462, 2017. https://doi.org/10.2172/1395455.
Civelek, Z. optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Eng. Sci. Technol. Int. J. 23 (1,1–9). https://doi.org/10.1016/j.jestch.2019.04.010 (2020).
Gouda, E. A new design of magnetic gear for wind turbine. (Dept. E). Bull. Fac. Eng. Mansoura Univ. 39 (1,1–6). https://doi.org/10.21608/bfemu.2020.103088 (2020).
Bharani, R., Sivaprakasam, A. & et al. A review analysis on performance and classification of wind turbine gearbox technologies. IETE J. Res. 68, 5,3341–3355. https://doi.org/10.1080/03772063.2020.1756936 (2022).
Ji, T. K., Baek, S. W. & et al. optimal design of a coaxial magnetic gear considering thermal demagnetization and structural robustness for torque density enhancement. Actuators 15 (1,59). https://doi.org/10.3390/act15010059 (2026).
Cheng, J., Zhang, W., Yin, X., Ding, F. & et al. Multi-objective optimization and analysis of divided-layer varying-network magnetic circuit based axial field flux-switching magnetic gear composite motors. J. Power Electron. 25 (3), 458–468. https://doi.org/10.1007/s43236-024-00900-7 (2025).
Zhao, H., Liu, C., Dong, Z., Huang, R., Li, X. & et al. design and optimization of a magnetic-geared direct-drive machine with V-shaped permanent magnets for ship propulsion. IEEE Trans. Transp. Electrification. 8 (2), 1619–1633. https://doi.org/10.1109/TTE.2021.3124891 (2022).
Shoaei, A., Farshbaf-Roomi, F., Wang, Q. & et al. Surrogate-based multi-objective optimization of flux-focusing Halbach coaxial magnetic gear. Energies 17 (3,608). https://doi.org/10.3390/en17030608 (2024).
Sedak, M. & Rosić, M. Rosić, Multi-Objective hybrid sailfish optimization algorithm for planetary gearbox and mechanical engineering design optimization problems. CMES 142 (2), 2111–2145. https://doi.org/10.32604/cmes.2025.059319 (2025).
Sepaseh, J., Rostami, N., Feyzi, M. R. & Sharifian, M. B. B. optimal design of an axial magnetic gear by using particle swarm optimisation method. IET Electr. Power Appl. 16 (6), 723–735. https://doi.org/10.1049/elp2.12189 (2022).
Kassab, Y., Ghanem, A., Gouda, E. & et al. analysis of a coaxial magnetic gear optimally designed using particle swarm optimization. Mansoura Eng. J. 49 (4). https://doi.org/10.58491/2735-4202.3206 (2024).
Ruiz-Ponce, G., Arjona, M. A. & Hernandez, C. Escarela-Perez, design optimization of an axial flux magnetic gear by using reluctance network modeling and genetic algorithm. Energies 16 (4,1852). https://doi.org/10.3390/en16041852 (2023).
Xiao, K. et al. Intelligent calibration of wind turbine gearbox dynamic model by integrating LSTM agent model and GA-PSO algorithm », Journal of Vibration and Control,10775463251341370, mai., (2025). https://doi.org/10.1177/10775463251341370.
Hasan Nehal, T. & Hamanah, W. M. Ali Abido, advancements in optimization techniques for active magnetic bearing systems: current trends and future directions. IEEE Access. 13, 111392–111419. https://doi.org/10.1109/ACCESS.2025.3575250 (2025).
Yang, E. et al. design and comparison of permanent magnetic gear and REBCO superconductor magnetic gear. Progress Superconductivity Cryogenics. 26 (4), 63–67. https://doi.org/10.9714/psac.2024.26.4.063 (2024).
C. G, Design Optimization of Power Take-Off Gearbox Using Multi-Objective Genetic Algorithm: NSGA-II », in Epicyclic Gearing, CRC, (2025).
Kovalenko, M. A., Kovalenko, I. Y., Tkachuk, I. V., Harford, A. G. & Tsyplenkov, D. V. mathematical modeling of a magnetic gear for an autonomous wind turbine. Nauk. Visn nat. Hirn univ. 2, 88–95. https://doi.org/10.33271/nvngu/2024-2/088 (2024).
Swain, A., Liu, C. & Pong, W. T. Modeling of wind turbine drive trains for finite element analysis through co-simulation. IEEE Trans. Magn. 59 (11). https://doi.org/10.1109/TMAG.2023.3314374 (2023).
Joseph Sunday Omokhoya. Finite Element Analysis for the Development of a high-efficiency Novel dual-stator Electric Generator for Renewable Energy Conversion applications - ProQuest, University of Alaska Fairbanks.
Xiao, K. et al. Intelligent calibration of wind turbine gearbox dynamic model by integrating LSTM agent model and GA-PSO algorithm. J. Vib. Control. 10775463251341370 https://doi.org/10.1177/10775463251341370 (2025).
Sun, Z., Zheng, C., Sun, X., Hou, X., Yang, Y. & et al. dual multi-objective optimization design method for compliant guide mechanism. Struct. Multidisc Optim. 67 (5,75). https://doi.org/10.1007/s00158-024-03793-z (2024).
Dragan, R. S., Barrett, R., Calverley, S. & Moreu, J. Atallah, Pseudo-direct-drive electrical machine for a floating marine turbine. IEEE Trans. Magn. 58 (2). https://doi.org/10.1109/TMAG.2021.3075904 (2022).
Grebenikov, V., Podoltsev, O., Tazhibaev, А., Arynov, N., Sakhno, O. & et al. calculation of magnetic losses and energy efficiency of a magnetic gearbox with a modulated magnetic field. Vidnovluvana Energetika. 1 (80), 92–99. https://doi.org/10.36296/1819-8058.2025.1(80 (2025).
Hazra,Kamat, S., Bhattacharya, S., Ouyang, W., Englebretson, S. & et al. power conversion with a magnetically-geared permanent magnet generator for low-speed wave energy converter. IEEE Trans. Ind. Appl. 56 (5), 5308–5318. https://doi.org/10.1109/TIA.2020.2997640 (sept. 2020).
Lee, J., Chang, J. & et al. analysis of the vibration characteristics of coaxial magnetic gear. IEEE Trans. Magn. 53 (6). https://doi.org/10.1109/TMAG.2017.2665660 (2017).
Qin, Q., Qiu, Y., Cai, B. & et al. optimization design and dynamic characteristics analysis of multistage magnetic gearbox for MW-scale wind turbine. J. Electr. Eng. Technol. 18 (4), 2969–2981. https://doi.org/10.1007/s42835-023-01409-y (2023).
Kong, X., Yang, Z. & et al. Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm. Sci. Rep. 15 (1,22982). https://doi.org/10.1038/s41598-025-07655-6 (2025).
El-Nemr, M., Afifi, M., Rezk, H., Ibrahim, M. & et al. finite element based overall optimization of switched reluctance motor using multi-objective genetic algorithm (NSGA-II). Mathematics 9 (5,576). https://doi.org/10.3390/math9050576 (2021).
Abdeljalil, D., Chaieb, M., Benhadj, N., Krichen, M., Neji, R. & et al. design and optimization of permanent magnet synchronous generator dedicated to direct-drive, high power wind turbine. Wind Eng. 46 (3,737–758). https://doi.org/10.1177/0309524X211046379 (2022).
Wang, Z., Gong, J., Liu, B. & et al. Multi-objective optimization of the Hollow shaft direct drive motor. Adv. Mech. Eng. 15 (3,16878132231163079). https://doi.org/10.1177/16878132231163079 (2023).
Ji, J., Yang, Y., Ling, Z. & Zhao, W. et al. Multi-objective optimization of interior permanent magnet machine for heavy-duty vehicle direct-drive applications », IEEE Transactions on Energy Conversion, 37,3,1946–1954, (2022). https://doi.org/10.1109/TEC.2022.3155160.
Li, W., Wang, D., Xing, Z., Sun, C. & et al. research on the torque density optimization of a semi-embedded permanent magnet wind turbine based on the non-dominated sorting genetic algorithm Ii and magnetic pole offset. Energies 17 (24,6415). https://doi.org/10.3390/en17246415 (2024).
Sethuraman, L. et K. L. Dykes, generatorse: a sizing tool for variable-speed wind turbine generators », National renewable energy laboratory (NREL), Golden, CO (United States), NREL/TP–5000–66462, 2017. https://doi.org/10.2172/1395455.
Civelek, Z. optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Eng. Sci. Technol. Int. J. 23 (1,1–9). https://doi.org/10.1016/j.jestch.2019.04.010 (2020).
Gouda, E. A new design of magnetic gear for wind turbine. (Dept. E). Bull. Fac. Eng. Mansoura Univ. 39 (1,1–6). https://doi.org/10.21608/bfemu.2020.103088 (2020).
Bharani, R., Sivaprakasam, A. & et al. A review analysis on performance and classification of wind turbine gearbox technologies. IETE J. Res. 68, 5,3341–3355. https://doi.org/10.1080/03772063.2020.1756936 (2022).
Ji, T. K., Baek, S. W. & et al. optimal design of a coaxial magnetic gear considering thermal demagnetization and structural robustness for torque density enhancement. Actuators 15 (1,59). https://doi.org/10.3390/act15010059 (2026).
Cheng, J., Zhang, W., Yin, X., Ding, F. & et al. Multi-objective optimization and analysis of divided-layer varying-network magnetic circuit based axial field flux-switching magnetic gear composite motors. J. Power Electron. 25 (3), 458–468. https://doi.org/10.1007/s43236-024-00900-7 (2025).
Zhao, H., Liu, C., Dong, Z., Huang, R., Li, X. & et al. design and optimization of a magnetic-geared direct-drive machine with V-shaped permanent magnets for ship propulsion. IEEE Trans. Transp. Electrification. 8 (2), 1619–1633. https://doi.org/10.1109/TTE.2021.3124891 (2022).
Shoaei, A., Farshbaf-Roomi, F., Wang, Q. & et al. Surrogate-based multi-objective optimization of flux-focusing Halbach coaxial magnetic gear. Energies 17 (3,608). https://doi.org/10.3390/en17030608 (2024).
Sedak, M. & Rosić, M. Rosić, Multi-Objective hybrid sailfish optimization algorithm for planetary gearbox and mechanical engineering design optimization problems. CMES 142 (2), 2111–2145. https://doi.org/10.32604/cmes.2025.059319 (2025).
Sepaseh, J., Rostami, N., Feyzi, M. R. & Sharifian, M. B. B. optimal design of an axial magnetic gear by using particle swarm optimisation method. IET Electr. Power Appl. 16 (6), 723–735. https://doi.org/10.1049/elp2.12189 (2022).
Kassab, Y., Ghanem, A., Gouda, E. & et al. analysis of a coaxial magnetic gear optimally designed using particle swarm optimization. Mansoura Eng. J. 49 (4). https://doi.org/10.58491/2735-4202.3206 (2024).
Ruiz-Ponce, G., Arjona, M. A. & Hernandez, C. Escarela-Perez, design optimization of an axial flux magnetic gear by using reluctance network modeling and genetic algorithm. Energies 16 (4,1852). https://doi.org/10.3390/en16041852 (2023).
Xiao, K. et al. Intelligent calibration of wind turbine gearbox dynamic model by integrating LSTM agent model and GA-PSO algorithm », Journal of Vibration and Control,10775463251341370, mai., (2025). https://doi.org/10.1177/10775463251341370.
Hasan Nehal, T. & Hamanah, W. M. Ali Abido, advancements in optimization techniques for active magnetic bearing systems: current trends and future directions. IEEE Access. 13, 111392–111419. https://doi.org/10.1109/ACCESS.2025.3575250 (2025).
Yang, E. et al. design and comparison of permanent magnetic gear and REBCO superconductor magnetic gear. Progress Superconductivity Cryogenics. 26 (4), 63–67. https://doi.org/10.9714/psac.2024.26.4.063 (2024).
C. G, Design Optimization of Power Take-Off Gearbox Using Multi-Objective Genetic Algorithm: NSGA-II », in Epicyclic Gearing, CRC, (2025).
Kovalenko, M. A., Kovalenko, I. Y., Tkachuk, I. V., Harford, A. G. & Tsyplenkov, D. V. mathematical modeling of a magnetic gear for an autonomous wind turbine. Nauk. Visn nat. Hirn univ. 2, 88–95. https://doi.org/10.33271/nvngu/2024-2/088 (2024).
Swain, A., Liu, C. & Pong, W. T. Modeling of wind turbine drive trains for finite element analysis through co-simulation. IEEE Trans. Magn. 59 (11). https://doi.org/10.1109/TMAG.2023.3314374 (2023).
Joseph Sunday Omokhoya. Finite Element Analysis for the Development of a high-efficiency Novel dual-stator Electric Generator for Renewable Energy Conversion applications - ProQuest, University of Alaska Fairbanks.
Xiao, K. et al. Intelligent calibration of wind turbine gearbox dynamic model by integrating LSTM agent model and GA-PSO algorithm. J. Vib. Control. 10775463251341370 https://doi.org/10.1177/10775463251341370 (2025).
Sun, Z., Zheng, C., Sun, X., Hou, X., Yang, Y. & et al. dual multi-objective optimization design method for compliant guide mechanism. Struct. Multidisc Optim. 67 (5,75). https://doi.org/10.1007/s00158-024-03793-z (2024).
Dragan, R. S., Barrett, R., Calverley, S. & Moreu, J. Atallah, Pseudo-direct-drive electrical machine for a floating marine turbine. IEEE Trans. Magn. 58 (2). https://doi.org/10.1109/TMAG.2021.3075904 (2022).
Grebenikov, V., Podoltsev, O., Tazhibaev, А., Arynov, N., Sakhno, O. & et al. calculation of magnetic losses and energy efficiency of a magnetic gearbox with a modulated magnetic field. Vidnovluvana Energetika. 1 (80), 92–99. https://doi.org/10.36296/1819-8058.2025.1(80 (2025).
Hazra,Kamat, S., Bhattacharya, S., Ouyang, W., Englebretson, S. & et al. power conversion with a magnetically-geared permanent magnet generator for low-speed wave energy converter. IEEE Trans. Ind. Appl. 56 (5), 5308–5318. https://doi.org/10.1109/TIA.2020.2997640 (sept. 2020).
Lee, J., Chang, J. & et al. analysis of the vibration characteristics of coaxial magnetic gear. IEEE Trans. Magn. 53 (6). https://doi.org/10.1109/TMAG.2017.2665660 (2017).
Qin, Q., Qiu, Y., Cai, B. & et al. optimization design and dynamic characteristics analysis of multistage magnetic gearbox for MW-scale wind turbine. J. Electr. Eng. Technol. 18 (4), 2969–2981. https://doi.org/10.1007/s42835-023-01409-y (2023).
Kong, X., Yang, Z. & et al. Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm. Sci. Rep. 15 (1,22982). https://doi.org/10.1038/s41598-025-07655-6 (2025).
El-Nemr, M., Afifi, M., Rezk, H., Ibrahim, M. & et al. finite element based overall optimization of switched reluctance motor using multi-objective genetic algorithm (NSGA-II). Mathematics 9 (5,576). https://doi.org/10.3390/math9050576 (2021).
Abdeljalil, D., Chaieb, M., Benhadj, N., Krichen, M., Neji, R. & et al. design and optimization of permanent magnet synchronous generator dedicated to direct-drive, high power wind turbine. Wind Eng. 46 (3,737–758). https://doi.org/10.1177/0309524X211046379 (2022).
Wang, Z., Gong, J., Liu, B. & et al. Multi-objective optimization of the Hollow shaft direct drive motor. Adv. Mech. Eng. 15 (3,16878132231163079). https://doi.org/10.1177/16878132231163079 (2023).
Ji, J., Yang, Y., Ling, Z. & Zhao, W. et al. Multi-objective optimization of interior permanent magnet machine for heavy-duty vehicle direct-drive applications », IEEE Transactions on Energy Conversion, 37,3,1946–1954, (2022). https://doi.org/10.1109/TEC.2022.3155160.
Li, W., Wang, D., Xing, Z., Sun, C. & et al. research on the torque density optimization of a semi-embedded permanent magnet wind turbine based on the non-dominated sorting genetic algorithm Ii and magnetic pole offset. Energies 17 (24,6415). https://doi.org/10.3390/en17246415 (2024).
Contributed Indexing:
Keywords: GA; IPDD-PMSG; Magnetic gearbox; Multi-objective optimization; PSO; Wind turbine
Entry Date(s):
Date Created: 20260221 Latest Revision: 20260221
Update Code:
20260222
DOI:
10.1038/s41598-026-40096-3
PMID:
41723251
Database:
MEDLINE
Weitere Informationen
Magnetic gearboxes (MGs) are increasingly explored in wind turbines as a reliable alternative to mechanical gearboxes, which suffer failures and costly maintenance. By integrating MG with Permanent Magnet Synchronous Generator, an Integrated Pseudo-Direct-Drive PMSG (IPDD-PMSG) is achieved, offering higher efficiency, contact-free operation, and improved system reliability. The proposed design improved the performance of the IPDD-PMSG systems in torque and efficiency for 2 MW wind turbines. A multi-objective optimization is implemented to achieve maximum volumetric torque density (VTD) as well as minimum cost. Both Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) heuristics methods of optimization are investigated in order to reach the best algorithm. Results showed that GA offers better convergence and higher-performing solutions, while PSO ensures a greater diversity of cost/VTD trade-offs. Thus, the proposed methodology enables optimized and balanced design systems and offers a significant improvement in VTD and cost of the system. The finite element approach verifies the geometry using the variables found by optimization.
(© 2026. The Author(s).)
Declarations. Competing interests: The authors declare no competing interests.