How to reduce the cogging torque of the integrated propeller motor is an important means to improve its noise performance because cogging torque is one of the key factors causing torque ripple. We proposed a method to reduce the cogging torque by optimizing the size of the Halbach array’s auxiliary pole. First, an analytical model for the airgap magnetic field of Halbach array based on different dimensions (including the circumference ratio and the radial thickness) of the auxiliary pole is given. Then the finite element method is used to verify the analytical model. On the basis, we calculated the cogging torque of different size of auxiliary poles as sample data by combining different circumference ratio and radial thickness. Furthermore, using the two-variable single-objective neural network genetic optimization algorithm based on Backpropagation (BP), we obtain the optimal size of the auxiliary pole. Finally, comparing the motor cogging torque and torque ripple before and after optimization indicated that the cogging torque and torque ripple are effectively reduced after optimizing the size of the auxiliary pole.

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Abstract:A rim driven thruster (RDT) is an integrated deep-sea motor thruster that has been widely studied. In order to improve the performance of RDT, a novel RDT motor with a modular stator is proposed in this paper. The electromagnetic performance of the new RDT motor is analyzed by the finite element method (FEM). The influence of structure parameters on the electromagnetic performance of the new RDT motor are analyzed in detail. It is shown that the effect of additional tooth width and pole arc coefficient on the electromagnetic performance of the stator modular RDT motor is significant. To obtain the optimal design with a maximum average electromagnetic torque and minimum torque fluctuation ratio, a multi-objective optimization design method combining the non-dominated sorting genetic algorithm II (NSGA-II), Kriging method and FEM is presented in this paper. A set of Pareto optimal solutions is obtained, and the optimal design point is selected from the Pareto fronts. Compared with the initial design, the average electromagnetic torque of the optimized model is improved by 16.591% and the fluctuation ratio is reduced to 3.18%.

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