PROJECT TITLE :

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

ABSTRACT:

This paper focuses on the optimal structural style 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. 1st, 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 like iron reluctances. A variety of style considerations are also presented to attain more practical results. Genetic algorithm is then utilized to optimize the lifting force while reducing the system power loss. Moreover, 3-D finite element technique (FEM) is used within the analyses and it's shown that the results calculated from the proposed model match well with those obtained from FEM. Moreover, superiorities of the implemented model over the existing approaches are demonstrated. The outcomes show that the proposed methodology has increased the magnetic force, while considerably reducing the suspension power loss compared with those in the traditional pure electromagnet structure and in a previously proposed hybrid structure.