Speed-based multiobjective optimisation of a cage-secondary permanent magnet linear eddy current brake

References

• Adly, A. A., & Abd-El-Hafiz, S. K. (2007). Speed-range-based optimization of nonlinear electromagnetic braking systems. IEEE Transactions on Magnetics, 43(6), 2606–2608. https://doi.org/10.1109/TMAG.2007.893411
   Web of Science ®Google Scholar
• Chen, C., Xu, J., & Wu, X. (2019). Analytical calculation of braking force of super-high-speed maglev eddy current braking system. 22nd international conference on electrical machines and systems (pp. 1–5). IEEE. https://doi.org/10.1109/ICEMS.2019.8921559
   Google Scholar
• Cheng, H., Wang, Z., Ma, L., Liu, X., & Wei, Z. (2021). Multi-task pruning via filter index sharing: A many-objective optimization approach. Cognitive Computation, 13(4), 1070–1084. https://doi.org/10.1007/s12559-021-09894-x
   Web of Science ®Google Scholar
• Cho, S., Liu, H., Ahn, H., Lee, J., & Lee, H. (2017). Eddy current brake with a two-layer structure: calculation and characterization of braking performance. IEEE Transactions on Magnetic, 53(11), 1–5. DOI: 10.1109/TMAG.2017.2707555
   Web of Science ®Google Scholar
• Ding, D., Wang, Z., & Han, Q.-L. (2020). A set-membership approach to event-triggered filtering for general nonlinear systems over sensor networks. IEEE Transactions on Automatic Control, 65(4), 1792–1799. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Edwards, J. D., Jayawant, B. V., & Dawson, W. R. C. (1999). Permanent-magnet linear Eddy-current brake with a non-magnetic reaction plate. IEE Proceedings-Electric Power Applications, 146(6), 627–631. https://doi.org/10.1049/ip-epa:19990574
   Google Scholar
• Gulec, M., Aydin, M., Nerg, J., Lindh, P., & Pyrhönen, J. J. (2019). Nonlinear multidisciplinary design approach for axial-flux eddy current brakes. IEEE Transactions on Energy Conversion, 34(4), 1917–1927. https://doi.org/10.1109/TEC.60
   Web of Science ®Google Scholar
• Gulec, M., Aydin, M., Nerg, J., Lindh, P., & Pyrhönen, J. J. (2021). Magneto-thermal analysis of an axial-flux permanent-magnet-assisted Eddy-current brake at high-temperature working conditions,. IEEE Transactions on Industrial Electronics, 68(6), 5112–5121. https://doi.org/10.1109/TIE.41
   Web of Science ®Google Scholar
• Jin, Y., Kou, B., Li, L., & Pan, D. (2022). Fluid flow and thermal analysis of an axial flux permanent magnet eddy current brake. IEEE Transactions on Vehicular Technology, 71(1), 260–268. https://doi.org/10.1109/TVT.2021.3127693
   Web of Science ®Google Scholar
• Karakoc, K., Suleman, A., & Park, E. J (2014). Optimized braking torque generation capacity of an eddy current brake with the application of time-varying magnetic fields. IEEE Transactions on Vehicular Technology, 63(4), 1530–1538. https://doi.org/10.1109/TVT.2013.2286097
   Web of Science ®Google Scholar
• Kou, B., Chen, W., & Jin, Y (2021). A novel cage-secondary permanent magnet linear eddy current brake with wide speed range and its analytical model. IEEE Transactions on Industrial Electronics, 69(7), 7130–7139. https://doi.org/10.1109/TIE.2021.3097603.
   Web of Science ®Google Scholar
• Kou, B., Jin, Y., Zhang, H., Zhang, L., & Zhang, H. (2014). Analysis and design of hybrid excitation linear eddy current brake. IEEE Transactions on Energy Conversion, 29(2), 496–506. https://doi.org/10.1109/TEC.2014.2307164
   Web of Science ®Google Scholar
• Liu, L., Ma, L., Wang, Y., Zhang, J., & Bo, Y. (2020). Distributed set-membership filtering for time-varying systems under constrained measurements and replay attacks. Journal of the Franklin Institute-Engineering and Applied Mathematics, 357(8), 4983–5003. https://doi.org/10.1016/j.jfranklin.2020.01.029
   Web of Science ®Google Scholar
• Liu, W., Wang, Z., Yuan, Y., Zeng, N., Hone, K., & Liu, X. (2021). A novel sigmoid-function-based adaptive weighted particle swarm optimizer. IEEE Transactions on Cybernetics, 51(2), 1085–1093. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Liu, W., Wang, Z., Zeng, N., Yuan, Y., F. E. Alsaadi, & Liu, X. (2020). A novel randomised particle swarm optimizer. International Journal of Machine Learning and Cybernetics, 12(2), 529–540. https://doi.org/10.1007/s13042-020-01186-4
   Web of Science ®Google Scholar
• Lubin, T., & Rezzoug, A. (2015). 3-D analytical model for axial-flux Eddy-current couplings and brakes under steady-state conditions. IEEE Transactions on Magnetics, 51(10), 1–12. https://doi.org/10.1109/TMAG.2015.2455955
   Web of Science ®Google Scholar
• Ma, C., & Qu, L. (2015). Multiobjective optimization of switched reluctance motors based on design of experiments and particle swarm optimization. IEEE Transactions on Energy Conversion, 30(3), 1144–1153. https://doi.org/10.1109/TEC.2015.2411677
   Web of Science ®Google Scholar
• Mohammadi, S., Mirsalim, M., & Vaez-Zadeh, S. (2014). Nonlinear modeling of Eddy-current couplers. IEEE Transactions on Energy Conversion, 29(1), 224–231. https://doi.org/10.1109/TEC.2013.2288948
   Web of Science ®Google Scholar
• Qu, B., Wang, Z., Shen, B., & Dong, H. (2021). Distributed state estimation for renewable energy microgrids with sensor saturations. Automatica, 131, 109730. https://doi.org/10.1016/j.automatica.2021.109730
   Web of Science ®Google Scholar
• Sattarov, R. R., Fedosov, E. M., Tumanov, A. A., & Ismagilov, R. R. (2019). Experimental studies of torque-speed characteristics of eddycurrent brakes with slotted disk rotor. International Conference on Industrial Engineering, Applications and Manufacturing, 11(9), 1–5. https://doi.org/10.1109/ICIEAM.2019.8743071
   Google Scholar
• Shin, K., Park, H., Cho, H., & Choi, J (2018). Semi-three-dimensional analytical torque calculation and experimental testing of an eddy current brake with permanent magnets. IEEE Transactions on Applied Superconductivity, 28(3), 1–5. https://doi.org/10.1109/TASC.2018.2795010
   Web of Science ®Google Scholar
• Song, J., Wang, Z., Niu, Y., & Dong, H. (2021). Genetic-algorithm-assisted sliding-mode control for networked state-saturated systems over hidden Markov fading channels. IEEE Transactions on Cybernetics, 51(7), 3664–3675. https://doi.org/10.1109/TCYB.2020.2980109
   PubMed Web of Science ®Google Scholar
• Tian, E., Wang, Z., Zou, L., & Yue, D. (2019). Chance-constrained H∞ control for a class of time-varying systems with stochastic nonlinearities: The finite-horizon case. Automatica, 107, 296–305. https://doi.org/10.1016/j.automatica.2019.05.039
   Web of Science ®Google Scholar
• Tian, J., Li, D., Ning, K., & Ye, L. (2020). A timesaving transient magneto-thermal coupling model for the eddy current brake. IEEE Transactions on Vehicular Technology, 69(10), 10832–10841. https://doi.org/10.1109/TVT.25
   Web of Science ®Google Scholar
• Wang, M., Wang, Z., Chen, Y., & Sheng, W. (2020). Event-based adaptive neural tracking control for discrete-time stochastic nonlinear systems: A triggering threshold compensation strategy. IEEE Transactions on Neural Networks and Learning Systems, 31(6), 1968–1981. https://doi.org/10.1109/TNNLS.5962385
   PubMed Web of Science ®Google Scholar
• Wang, M., Wang, Z., Dong, H., & Han, Q.-L. (2021). A novel framework for backstepping-based control of discrete-time strict-feedback nonlinear systems with multiplicative noises. IEEE Transactions on Automatic Control, 66(4), 1484–1496. https://doi.org/10.1109/TAC.2020.2995576
   Web of Science ®Google Scholar
• Wang, P., & Chiueh, S. J (1998). Analysis of Eddy-current brakes for high-speed railway. IEEE Transactions on Magnetics, 34(4), 1237–1239. https://doi.org/10.1109/20.706507
   Web of Science ®Google Scholar
• Williamson, S., & Begg, M. C. (1986). Calculation of the resistance of induction motor end rings. IEE Proceedings B (Electric Power Applications), 133(2), 54–60. https://doi.org/10.1049/ip-b.1986.0010
   Google Scholar
• Yang, J., Ma, L., Chen, Y., & Yi, X (2022). l2– l∞ state estimation for continuous stochastic delayed neural networks via memory event-triggering strategy. International Journal of Systems Science, 53(13), 2742–2757. https://doi.org/10.1080/00207721.2022.2055192.
   Web of Science ®Google Scholar
• Zeng, N., Wang, Z., Liu, W., Zhang, H., Hone, K., & Liu, X (2020). A dynamic neighborhood-based switching particle swarm optimization algorithm. IEEE Transactions on Cybernetics, 52(9), 9290–9301. https://doi.org/10.1109/TCYB.2020.3029748.
   Web of Science ®Google Scholar
• Zhang, B., Peng, T., Chen, Q., Cao, Q., Ji, K., Shuang, B., Ye, J., & Li, L. (2012). 3-D nonlinear transient analysis and design of eddy current brake for high-speed trains. International Journal of Applied Electromagnetics and Mechanics, 40(3), 205–214. https://doi.org/10.3233/JAE-2012-1585
   Web of Science ®Google Scholar
• Zuo, L., Chen, X., & Nayfeh, S. (2011). Design and analysis of a new type of electromagnetic damper with increased energy density. Journal of Vibration and Acoustics, 133(4), 041006. https://doi.org/10.1115/1.4003407
   Google Scholar