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The traditional optimal design of a transverse magnetic field motor mainly uses the electromagnetic relational formulas and the finite element analysis to empirically select its structural parameters, therefore making it difficult to obtain the global optimal solution of each parameter and meeting the requirements for multi-objective optimization. This paper suggests a hybrid algorithm of harmony search and differential evolution and introduces the elite retention strategy to improve the hybrid algorithm. It presents the principles of the hybrid algorithm, and then the algorithm performance test is used to verify the superiority of the hybrid algorithm. The electromagnetic analysis demonstrates the influence of the main dimensional parameters of the transverse magnetic field motor on its maximum torque density, therefore providing the basis for its optimal design. Jointly with the hybrid algorithm, the maximum torque density and the production cost are used as the objective function to optimize the transverse magnetic field motor under two groups of weighted coefficients. The simulation results show that the maximum torque density of the transverse magnetic field motor optimized with the hybrid algorithm is larger compared with the prototype motor but its production cost is lower.

Optimal design of transverse field motor based on hybrid algorithm of harmony search and differential evolution