Design Optimization of Magnetic Gears Using Mesh Adjustable Finite-Element Algorithm for Improved Torque

Magnetic gears (MGs) are devices which operate through the interaction of magnetic fields produced by multipole magnets to transmit torque with high efficiency. Compared with mechanical gears, it requires no moving contact for the force transmission, hence there are no mechanical fatigue and no mechanical loss and less acoustic noise. There is no need for lubrication and hence MG requires minimal maintenance. However, the heavy use of permanent magnetic (PM) materials leads to a high production cost. In this paper, a novel mesh adjustable finite-element algorithm is proposed to optimize the magnetic gear dimensions in order to maximize the torque output for a given amount of PMs. With the proposed mesh adjustable finite-element algorithm, the coordinates of mesh nodes are moved according to dimensional changes, without compromising the mesh quality. The merit is that no re-mesh is required during the process of optimization, which can significantly reduce the computing time while retaining the robustness of the algorithm. By combining the proposed approach with particle swarm optimization (PSO) algorithm, a reliable convergence to the finding of global optimum is achieved. This proposed method is applied to optimize the dimensions of a coaxial magnetic gear with surface mounted PMs. Optimal results confirm the validity and effectiveness of the proposed algorithm.