Abstract
The onboard superconducting magnets and null-flux coils (NFCs) on the track side are the crucial components for realizing the null-flux superconducting electrodynamic suspension (EDS). In this article, the multiobjective optimization of a null-flux EDS system was investigated to improve the performance using the nondominated sorting genetic algorithm-II (NSGA-II) method. First, a precise mathematical model of the superconducting EDS was established by adopting mutual inductance calculation method we proposed before. Then, the comprehensive sensitive analysis was carried out to analyze the influence of variables on different objectives. The ratio of levitation force to drag force (drag ratio), the ratio of levitation force to mass of NFCs (mass ratio) as well as the fluctuation of levitation force, were defined to be the optimization objectives. Third, an optimization scheme employing NSGA-II method was built, and the Pareto front was obtained. Afterward, the effectiveness of optimized results was verified by the finite element analysis. Finally, an equivalent experimental method was used to characterize the performance of a down-scale EDS system to confirm the proposed optimization methodology. To conclude, the optimal method can greatly improve the performance of EDS, and provide diverse design scheme choices.
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