Optimal design of electromagnet for Maglev vehicles using hybrid optimization algorithm

This paper introduces a new design method using a hybrid optimization algorithm for the electromagnet used in maglev transportation vehicles. Maglev system typically uses electromagnetic suspension, which is more advantageous than electro dynamic suspension. However, the structural constraints must be considered in the optimal design of an electromagnet for an electromagnetically suspended vehicle. In this study, a hybrid optimization algorithm based on the teaching–learning based optimization algorithm and clonal selection was used to design an electromagnet satisfying the structural constraints. The proposed method was verified by MATLAB simulations, which showed that the proposed method is more efficient than conventional methods.