Guoqing Liu

Multi-Objective Pareto Optimization of Electromagnetic Devices Exploiting Kriging With Lipschitzian Optimized Expected Improvement

This paper focuses on resolving the storage issue of correlation matrices generated by kriging surrogate models in the context of electromagnetic optimization problems with many design variables and multiple objectives. The suggested-improved kriging approach incorporating a direct algorithm is able to maintain memory requirements at a nearly constant level while offering high efficiency of searching for a global optimum. The feasibility and efficiency of this proposed methodology are demonstrated using an example of a classic two-variable analytic function and a new proposed benchmark TEAM multi-objective Pareto optimization problem.

Optimal design of a for middle-low-speed maglev trains

Abstract A middle-low-speed maglev train is supported by an electromagnetic force between the suspension electromagnet (EM) and the steel rail and is driven by a linear induction motor. The capability of the suspension system has a direct bearing on safety and the technical and economic performance of the train. This paper focuses on the dependence of the electromagnetic force on the structural configuration of the EM with the purpose of improving performance of a conventional EM. Finally, a novel configuration is proposed of a hybrid suspension magnet, which combines permanent magnets and coils, in order to increase the suspension force while reducing the suspension power loss.