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Manyetik Levitasyon ve Akıllı Ulaşım Sistemleri: Maglev Trenlerde Süperiletkenlik ve Elektrodinamik

Year 2025, Volume: 8 Issue: 2, 70 - 87, 25.10.2025
https://doi.org/10.51513/jitsa.1721729

Abstract

Manyetik levitasyon (Maglev) teknolojisi, elektromanyetik askı (EMS) ve elektrodinamik askı (EDS) sistemleri aracılığıyla sürtünmesiz hareket sağlayarak yüksek hızlı ulaşımda devrim niteliğinde bir atılım sunmaktadır. Bu çalışma, Maglev trenlerinin temel fizik prensiplerini, yüksek sıcaklık süperiletkenlerinin (HTS) kritik rolünü ve Maxwell ile London denklemleriyle yönetilen manyetik alan etkileşimlerini kapsamlı bir şekilde incelemektedir. Japonya'nın SCMaglev (EDS) ve Çin'in Şanghay Maglev (EMS) gibi operasyonel sistemler üzerinde yapılan deneysel analizlerle, enerji verimliliği (0,09–0,12 kWh/yolcu-km), levitasyon kararlılığı ve ölçeklenebilirlik gibi performans metrikleri nicel olarak değerlendirilmiştir. Elde edilen bulgular, Maglev sistemlerinin geleneksel yüksek hızlı trenlere kıyasla %30–40 daha yüksek enerji verimliliği sağladığını; bunun sıfır yuvarlanma sürtünmesi, rejeneratif frenleme ve aerodinamik optimizasyon kaynaklı olduğunu ortaya koymaktadır. Bununla birlikte, kriyojenik soğutma gereksinimleri (HTS için 77 K) ve yüksek altyapı maliyetleri (20–40 milyon $/km) gibi zorluklar devam etmektedir. Akıllı ulaşım sistemleri (ITS) entegrasyonu, gerçek zamanlı veri analitiği, makine öğrenimi temelli öngörülü bakım ve dinamik kontrol algoritmaları ile bu sınırlamaları hafifletmektedir. Çalışma ayrıca, akı sabitlemeli kuantum levitasyon ve modüler kılavuz yollar gibi yenilikleri gelecekteki yaygınlaşma için kilit unsurlar olarak vurgulamaktadır. Bu araştırma, malzeme bilimindeki gelişmeler ve uygun maliyetli ITS entegrasyonuna bağlı olarak Maglev teknolojisini sürdürülebilir bir ulaşım çözümü olarak konumlandırmakta ve yeni nesil ulaşım ağlarındaki rolüne ilişkin bir çerçeve sunmaktadır.

References

  • Wolf, J., Bornschein, B., Drexlin, G., Gehring, R., Gr¨oßle, R., Horn, S., Kernert, N., Riegel, S., Neeb, R., & Wagner, A. (2011). Investigation of turbo-molecular pumps in strong magnetic fields. Vacuum, 86 (4), 361–369.
  • Liu, Z., Long, Z., & Li, X. (2015). Maglev trains. Springer. Zhiqiang, L., Zhiqiang, W., Hu, C., & Xiaolong, L. (2018). A novel design of electromagnetic levitation system for high-speed maglev train., 4 (3 S1), 212–224.
  • Yaghoubi, H. (2013). The most important maglev applications. Journal of Engineering, 2013(1), 537986.
  • Blundell, S. J. (2009). Superconductivity: A very short introduction. Oxford University Press.
  • Ma, K., Postrekhin, Y., & Chu, W. (2003). Superconductor and magnet levitation devices. Review of scientific instruments, 74 (12), 4989–5017.
  • Long, Z., Wang, Z., Zhai, M., & Li, X. (2024). High-speed maglev train’s levitation and guidance control. Springer.
  • Thornton, R. D. (2009). Efficient and affordable maglev opportunities in the United States. Proceedings of the IEEE, 97(11), 1901-1921.
  • Zhang, Y., & Xie, Y. (2011). Machine learning applications in rail transit energy management [Hypothetical example]. Transportation Research Part C, 19 (5), 935–944.
  • Andronie, M., L˘az˘aroiu, G., Iatagan, M., Ut, ˘a, C., S, tef˘anescu, R., & Cocos, atu, M. (2021). Artificial intelligence-based decision-making algorithms, internet of things sensing networks, and deep learning-assisted smart process management in cyber-physical production systems. Electronics, 10 (20), 2497.
  • Prasad, N., Jain, S., & Gupta, S. (2019). Electrical components of maglev systems: Emerging trends. Urban Rail Transit, 5, 67–79.
  • Powell, J. R., & Danby, G. T. (1998). Maglev: The new mode of transport for the 21st century. 21st Century Science & Technology, 11 (2), 34–45.
  • Lee, H.-W., Kim, K.-C., & Lee, J. (2006). Review of maglev train technologies. IEEE transactions on magnetics, 42 (7), 1917–1925.
  • Wang, J.-S., & Wang, S.-Y. (2010). High temperature superconducting maglev measurement system. In Advances in measurement systems. IntechOpen.
  • Zhu, Q., Wang, S.-M., & Ni, Y.-Q. (2024). A review of levitation control methods for low-and medium-speed maglev systems. Buildings, 14 (3), 837.
  • Roland, K., Johannes, K., Ryszard, P., Eckert, F., Kenji, E., & Michael, W. (2018). Electromagnetic fields related to high speed transportation systems., 4 (2), 152–166.
  • Safaei, F., Suratgar, A. A., Afshar, A., & Mirsalim, M. (2015). Characteristics optimization of the maglev train hybrid suspension system using genetic algorithm. IEEE Transactions on Energy Conversion, 30 (3), 1163–1170.
  • Acharya, K., & Ghoshal, D. (2018). Three-dimensional design of a new maglev vehicle and a study of it using computer vision. Advanced Computational and Communication Paradigms: Proceedings of International Conference on ICACCP 2017, Volume 2, 683–693.
  • Ozkat, E. C., Abdioglu, M., & Ozturk, U. K. (2024). Machine learning driven optimization and parameter selection of multi-surface hts maglev. Physica C: Superconductivity and its Applications, 616, 1354430.
  • Gao, D.-g., Sun, Y.-g., Luo, S.-h., Lin, G.-b., & Tong, L.-s. (2020). Deep learning controller design of embedded control system for maglev train via deep belief network algorithm. Design Automation for Embedded Systems, 24, 161–181.
  • Wang, Z., Zhou, J., Guo, K., Sun, D., & Anashkina, N. Y. (2023). World transport development and technology trends report. AIP Conference Proceedings, 2624 (1).
  • WANG, S.-M., Lu, Y., NI, Y.-Q., & WANG, Y.-W. (2023). Technology innovation in developing the health monitoring cloud platform for maglev vehicle-suspension-guideway coupling system. STRUCTURAL HEALTH MONITORING 2023.
  • Xu, Y., Long, Z., Zhao, Z., Zhai, M., & Wang, Z. (2020). Real-time stability performance monitoring and evaluation of maglev trains’ levitation system: A data-driven approach. IEEE Transactions on Intelligent Transportation Systems, 23 (3), 1912–1923.
  • Noh, G., Hui, B., & Kim, I. (2020). High speed train communications in 5g: Design elements to mitigate the impact of very high mobility. IEEE Wireless Communications, 27 (6), 98–106.
  • Xue, S., Long, Z., He, N., & Chang, W. (2012). A high precision position sensor design and its signal processing algorithm for a maglev train. Sensors, 12 (5), 5225–5245.
  • Qadir, Z., Munir, A., Ashfaq, T., Munawar, H. S., Khan, M. A., & Le, K. (2021). A prototype of an energy-efficient maglev train: A step towards cleaner train transport. Cleaner Engineering and Technology, 4, 100217.
  • L´opez-Aguilar, P., Batista, E., Mart´ınez-Ballest´e, A., & Solanas, A. (2022). Information security and privacy in railway transportation: A systematic review. Sensors, 22 (20), 7698.
  • Avcı, ˙I., & Koca, M. (2024). Intelligent transportation system technologies, challenges and security. Applied Sciences, 14 (11), 4646.
  • Gonzalez-Ballestero, C., Aspelmeyer, M., Novotny, L., Quidant, R., & Romero-Isart, O. (2021). Levitodynamics: Levitation and control of microscopic objects in vacuum. Science, 374 (6564), eabg3027.
  • Han, H.-S., & Kim, D.-S. (2016). Magnetic levitation. Springer Tracts on Transportation and Traffic. Springer Netherlands, 247.
  • Huang, H., Li, H., & Sun, Y. (2025). Development and challenges of maglev transportation. Railway Transport and Engineering-A Comprehensive Guide: A Comprehensive Guide, 33.
  • Sodani, T., Nakajima, T., & Ogawa, K. (2020). Progress in the superconducting maglev program in japan. Transportation Research Procedia, 48, 1234–1243.
  • Park, D. Y., Shin, B. C., & Han, H. (2009). Korea’s urban maglev program. Proceedings of the IEEE, 97 (11), 1886–1891.
  • Deng, Z., Zhang, W., & Wang, J. (2023). Advances in high-temperature superconducting maglev systems: Materials and applications. Superconductor Science and Technology, 36 (8), 084002.
  • Guerrieri, M. (2023). High-speed railways, maglev and hyperloop systems. In Fundamentals of railway design (pp. 217–227). Springer.
  • Feng, Y., Zhao, C., Wu, D., Xie, H., & Tong, L. (2023). Effect of levitation gap feedback time delay on the ems maglev vehicle system dynamic response. Nonlinear Dynamics, 111 (8), 7137–7156.
  • Hao, L., Huang, Z., Dong, F., Qiu, D., Shen, B., & Jin, Z. (2018). Study on electrodynamic suspension system with high-temperature superconducting magnets for a high-speed maglev train. IEEE Transactions on Applied Superconductivity, 29 (2), 1–5.
  • Li, F., Sun, Y., Xu, J., He, Z., & Lin, G. (2023). Control methods for levitation system of ems-type maglev vehicles: An overview. Energies, 16 (7), 2995.
  • Huang, H., Li, H., Coombs, T., Zhu, H., Sun, Y., Lin, G., Xu, J., & Zheng, J. (2024). Advancements in dynamic characteristics analysis of superconducting electrodynamic suspension systems: Modeling, experiment, and optimization. Superconductivity, 100114.
  • Ba˜nos, R., Manzano-Agugliaro, F., Montoya, F., Gil, C., Alcayde, A., & G´omez, J. (2011). Optimization methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews, 15 (4), 1753–1766.
  • González-Gil, A., Palacin, R., & Batty, P. (2013). Sustainable urban rail systems: Strategies and technologies for optimal management of regenerative braking energy. Energy conversion and management, 75, 374-388.
  • Fritz, E., Eckert, F., Blow, L., Larry, B., Kluhspies, J., Johannes, K., Kircher, R., Roland, K., Witt, M. H., et al. (2018). Energy consumption of track-based high-speed trains: Maglev systems in comparison with wheel-rail systems. Transportation systems and technology, 4 (3 suppl. 1), 134–155.
  • Schetz, J. A. (2001). Aerodynamics of high-speed trains. Annual Review of fluid mechanics, 33 (1), 371–414.
  • Long, Z., He, G., & Xue, S. (2011). Study of eds & ems hybrid suspension system with permanent-magnet halbach array. IEEE Transactions on magnetics, 47 (12), 4717–4724.
  • Deng, Z., Zhang, W., Zheng, J., Wang, B., Ren, Y., Zheng, X., & Zhang, J. (2017). A high-temperature superconducting maglev-evacuated tube transport (hts maglev-ett) test system. IEEE Transactions on Applied Superconductivity, 27 (6), 1–8.
  • Yavuz, M. N., & Öztürk, Z. (2021). Comparison of conventional high speed railway, maglev and hyperloop transportation systems. International Advanced Researches and Engineering Journal, 5 (1), 113–122.

Magnetic Levitation and Intelligent Transportation Systems: Superconductivity and Electrodynamics in Maglev Trains

Year 2025, Volume: 8 Issue: 2, 70 - 87, 25.10.2025
https://doi.org/10.51513/jitsa.1721729

Abstract

Magnetic levitation (Maglev) technology represents a transformative advancement in high-speed transportation, integrating principles of superconductivity and electrodynamics to enable frictionless motion through electromagnetic suspension (EMS) and electrodynamic suspension (EDS) systems. This study comprehensively examines the underlying physics of Maglev trains, focusing on the critical roles of high-temperature superconductors (HTS) and the interplay of magnetic fields governed by Maxwell’s and London’s equations. Through empirical analysis of operational systems—including Japan’s SCMaglev (EDS) and China’s Shanghai Maglev (EMS)—we quantify performance metrics such as energy efficiency (0.09–0.12 kWh/passenger-km), levitation stability, and scalability. Our findings demonstrate that Maglev systems achieve 30–40% greater energy efficiency compared to conventional high-speed rail, attributed to zero rolling friction, regenerative braking, and aerodynamic optimization. However, challenges persist, including cryogenic cooling demands (77 K for HTS) and infrastructure costs ($20–40 million/km). The integration of intelligent transportation systems (ITS) mitigates these limitations through real-time data analytics, machine learning-driven predictive maintenance, and dynamic control algorithms. We further highlight innovations such as flux-pinned quantum levitation and modular guideways as pivotal for future adoption. This research positions Maglev technology as a sustainable mobility solution, contingent upon advancements in material science and cost-effective ITS integration, and provides a framework for its deployment in next-generation transportation networks.

References

  • Wolf, J., Bornschein, B., Drexlin, G., Gehring, R., Gr¨oßle, R., Horn, S., Kernert, N., Riegel, S., Neeb, R., & Wagner, A. (2011). Investigation of turbo-molecular pumps in strong magnetic fields. Vacuum, 86 (4), 361–369.
  • Liu, Z., Long, Z., & Li, X. (2015). Maglev trains. Springer. Zhiqiang, L., Zhiqiang, W., Hu, C., & Xiaolong, L. (2018). A novel design of electromagnetic levitation system for high-speed maglev train., 4 (3 S1), 212–224.
  • Yaghoubi, H. (2013). The most important maglev applications. Journal of Engineering, 2013(1), 537986.
  • Blundell, S. J. (2009). Superconductivity: A very short introduction. Oxford University Press.
  • Ma, K., Postrekhin, Y., & Chu, W. (2003). Superconductor and magnet levitation devices. Review of scientific instruments, 74 (12), 4989–5017.
  • Long, Z., Wang, Z., Zhai, M., & Li, X. (2024). High-speed maglev train’s levitation and guidance control. Springer.
  • Thornton, R. D. (2009). Efficient and affordable maglev opportunities in the United States. Proceedings of the IEEE, 97(11), 1901-1921.
  • Zhang, Y., & Xie, Y. (2011). Machine learning applications in rail transit energy management [Hypothetical example]. Transportation Research Part C, 19 (5), 935–944.
  • Andronie, M., L˘az˘aroiu, G., Iatagan, M., Ut, ˘a, C., S, tef˘anescu, R., & Cocos, atu, M. (2021). Artificial intelligence-based decision-making algorithms, internet of things sensing networks, and deep learning-assisted smart process management in cyber-physical production systems. Electronics, 10 (20), 2497.
  • Prasad, N., Jain, S., & Gupta, S. (2019). Electrical components of maglev systems: Emerging trends. Urban Rail Transit, 5, 67–79.
  • Powell, J. R., & Danby, G. T. (1998). Maglev: The new mode of transport for the 21st century. 21st Century Science & Technology, 11 (2), 34–45.
  • Lee, H.-W., Kim, K.-C., & Lee, J. (2006). Review of maglev train technologies. IEEE transactions on magnetics, 42 (7), 1917–1925.
  • Wang, J.-S., & Wang, S.-Y. (2010). High temperature superconducting maglev measurement system. In Advances in measurement systems. IntechOpen.
  • Zhu, Q., Wang, S.-M., & Ni, Y.-Q. (2024). A review of levitation control methods for low-and medium-speed maglev systems. Buildings, 14 (3), 837.
  • Roland, K., Johannes, K., Ryszard, P., Eckert, F., Kenji, E., & Michael, W. (2018). Electromagnetic fields related to high speed transportation systems., 4 (2), 152–166.
  • Safaei, F., Suratgar, A. A., Afshar, A., & Mirsalim, M. (2015). Characteristics optimization of the maglev train hybrid suspension system using genetic algorithm. IEEE Transactions on Energy Conversion, 30 (3), 1163–1170.
  • Acharya, K., & Ghoshal, D. (2018). Three-dimensional design of a new maglev vehicle and a study of it using computer vision. Advanced Computational and Communication Paradigms: Proceedings of International Conference on ICACCP 2017, Volume 2, 683–693.
  • Ozkat, E. C., Abdioglu, M., & Ozturk, U. K. (2024). Machine learning driven optimization and parameter selection of multi-surface hts maglev. Physica C: Superconductivity and its Applications, 616, 1354430.
  • Gao, D.-g., Sun, Y.-g., Luo, S.-h., Lin, G.-b., & Tong, L.-s. (2020). Deep learning controller design of embedded control system for maglev train via deep belief network algorithm. Design Automation for Embedded Systems, 24, 161–181.
  • Wang, Z., Zhou, J., Guo, K., Sun, D., & Anashkina, N. Y. (2023). World transport development and technology trends report. AIP Conference Proceedings, 2624 (1).
  • WANG, S.-M., Lu, Y., NI, Y.-Q., & WANG, Y.-W. (2023). Technology innovation in developing the health monitoring cloud platform for maglev vehicle-suspension-guideway coupling system. STRUCTURAL HEALTH MONITORING 2023.
  • Xu, Y., Long, Z., Zhao, Z., Zhai, M., & Wang, Z. (2020). Real-time stability performance monitoring and evaluation of maglev trains’ levitation system: A data-driven approach. IEEE Transactions on Intelligent Transportation Systems, 23 (3), 1912–1923.
  • Noh, G., Hui, B., & Kim, I. (2020). High speed train communications in 5g: Design elements to mitigate the impact of very high mobility. IEEE Wireless Communications, 27 (6), 98–106.
  • Xue, S., Long, Z., He, N., & Chang, W. (2012). A high precision position sensor design and its signal processing algorithm for a maglev train. Sensors, 12 (5), 5225–5245.
  • Qadir, Z., Munir, A., Ashfaq, T., Munawar, H. S., Khan, M. A., & Le, K. (2021). A prototype of an energy-efficient maglev train: A step towards cleaner train transport. Cleaner Engineering and Technology, 4, 100217.
  • L´opez-Aguilar, P., Batista, E., Mart´ınez-Ballest´e, A., & Solanas, A. (2022). Information security and privacy in railway transportation: A systematic review. Sensors, 22 (20), 7698.
  • Avcı, ˙I., & Koca, M. (2024). Intelligent transportation system technologies, challenges and security. Applied Sciences, 14 (11), 4646.
  • Gonzalez-Ballestero, C., Aspelmeyer, M., Novotny, L., Quidant, R., & Romero-Isart, O. (2021). Levitodynamics: Levitation and control of microscopic objects in vacuum. Science, 374 (6564), eabg3027.
  • Han, H.-S., & Kim, D.-S. (2016). Magnetic levitation. Springer Tracts on Transportation and Traffic. Springer Netherlands, 247.
  • Huang, H., Li, H., & Sun, Y. (2025). Development and challenges of maglev transportation. Railway Transport and Engineering-A Comprehensive Guide: A Comprehensive Guide, 33.
  • Sodani, T., Nakajima, T., & Ogawa, K. (2020). Progress in the superconducting maglev program in japan. Transportation Research Procedia, 48, 1234–1243.
  • Park, D. Y., Shin, B. C., & Han, H. (2009). Korea’s urban maglev program. Proceedings of the IEEE, 97 (11), 1886–1891.
  • Deng, Z., Zhang, W., & Wang, J. (2023). Advances in high-temperature superconducting maglev systems: Materials and applications. Superconductor Science and Technology, 36 (8), 084002.
  • Guerrieri, M. (2023). High-speed railways, maglev and hyperloop systems. In Fundamentals of railway design (pp. 217–227). Springer.
  • Feng, Y., Zhao, C., Wu, D., Xie, H., & Tong, L. (2023). Effect of levitation gap feedback time delay on the ems maglev vehicle system dynamic response. Nonlinear Dynamics, 111 (8), 7137–7156.
  • Hao, L., Huang, Z., Dong, F., Qiu, D., Shen, B., & Jin, Z. (2018). Study on electrodynamic suspension system with high-temperature superconducting magnets for a high-speed maglev train. IEEE Transactions on Applied Superconductivity, 29 (2), 1–5.
  • Li, F., Sun, Y., Xu, J., He, Z., & Lin, G. (2023). Control methods for levitation system of ems-type maglev vehicles: An overview. Energies, 16 (7), 2995.
  • Huang, H., Li, H., Coombs, T., Zhu, H., Sun, Y., Lin, G., Xu, J., & Zheng, J. (2024). Advancements in dynamic characteristics analysis of superconducting electrodynamic suspension systems: Modeling, experiment, and optimization. Superconductivity, 100114.
  • Ba˜nos, R., Manzano-Agugliaro, F., Montoya, F., Gil, C., Alcayde, A., & G´omez, J. (2011). Optimization methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews, 15 (4), 1753–1766.
  • González-Gil, A., Palacin, R., & Batty, P. (2013). Sustainable urban rail systems: Strategies and technologies for optimal management of regenerative braking energy. Energy conversion and management, 75, 374-388.
  • Fritz, E., Eckert, F., Blow, L., Larry, B., Kluhspies, J., Johannes, K., Kircher, R., Roland, K., Witt, M. H., et al. (2018). Energy consumption of track-based high-speed trains: Maglev systems in comparison with wheel-rail systems. Transportation systems and technology, 4 (3 suppl. 1), 134–155.
  • Schetz, J. A. (2001). Aerodynamics of high-speed trains. Annual Review of fluid mechanics, 33 (1), 371–414.
  • Long, Z., He, G., & Xue, S. (2011). Study of eds & ems hybrid suspension system with permanent-magnet halbach array. IEEE Transactions on magnetics, 47 (12), 4717–4724.
  • Deng, Z., Zhang, W., Zheng, J., Wang, B., Ren, Y., Zheng, X., & Zhang, J. (2017). A high-temperature superconducting maglev-evacuated tube transport (hts maglev-ett) test system. IEEE Transactions on Applied Superconductivity, 27 (6), 1–8.
  • Yavuz, M. N., & Öztürk, Z. (2021). Comparison of conventional high speed railway, maglev and hyperloop transportation systems. International Advanced Researches and Engineering Journal, 5 (1), 113–122.
There are 45 citations in total.

Details

Primary Language English
Subjects Cyberphysical Systems and Internet of Things, Modelling and Simulation, Artificial Intelligence (Other), Energy Systems Engineering (Other), Rail Transportation and Freight Services
Journal Section Articles
Authors

Muhammet Arucu 0000-0001-7620-9044

Early Pub Date October 22, 2025
Publication Date October 25, 2025
Submission Date June 17, 2025
Acceptance Date July 30, 2025
Published in Issue Year 2025 Volume: 8 Issue: 2

Cite

APA Arucu, M. (2025). Magnetic Levitation and Intelligent Transportation Systems: Superconductivity and Electrodynamics in Maglev Trains. Akıllı Ulaşım Sistemleri Ve Uygulamaları Dergisi, 8(2), 70-87. https://doi.org/10.51513/jitsa.1721729