Characteristics Optimization of the Maglev Train Hybrid Suspension System Using Genetic Algorithm

This paper focuses on the optimal structural design of a hybrid permanent-magnet-electro-magnetic suspension system (PEMS) for a magnetic levitation (Maglev) transportation system in order to decrease the suspension power loss. First, the nonlinear magnetic force expression of a PEMS system is obtained by developing the magnetic equivalent circuit of the hybrid structure. The proposed analytical framework accounts for leakage fluxes and material properties such as iron reluctances. A number of design considerations are also presented to attain more practical results. Genetic algorithm is then employed to optimize the lifting force while reducing the system power loss. Moreover, 3-D finite element method (FEM) is utilized in the analyses and it is shown that the results calculated from the proposed model match well with those obtained from FEM. In addition, superiorities of the implemented model over the existing approaches are demonstrated. The outcomes show that the proposed method has increased the magnetic force, while significantly reducing the suspension power loss compared with those in the conventional pure electromagnet structure and in a previously proposed hybrid structure.