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Computational study demonstrates efficient multi-objective optimization for magnetic levitation planar motors, highlighting maximum force output with minimal power dissipation and cost.
This paper proposes a fast and accurate electromagnetic optimization method for magnetic levitation planar motors (MLPMs). With the purpose of achieving the maximum force with the minimum power dissipation and cost, a multi-objective optimization is adopted for the MLPM. Furthermore, in order to improve the precision and reduce the computational burden, the levitation force expression in the objective function is analyzed through the numerical model. This model is built by the magnetic charge method and the Gaussian quadrature and implemented in parallel computation. According to the optimal objective, an intelligent optimization algorithm-particle swarm optimization (PSO)-is used to undertake the optimization variables of the planar motor for a global optimal solution. The precision and effectiveness of the proposed method are validated by both the finite-element method (FEM) commercial software COMSOL and a boundary element software program named Radia. The comparative results with other optimization methods are also presented to highlight the performance of the proposed optimization method.
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Zheng et al. (2019) studied this question.
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