Multi-Objective Optimization Design of Surface Mount Permanent Magnet Synchronous Motor for UAV

In order to address the vibration noise generated during the operation of the drone due to the operation of the motor, this paper selects the key structural parameters inside the motor as the optimization variables, and uses the average output torque, torque ripple and load air gap magnetic density as the optimization objectives for multi-objective optimization design. First, the excitation source of the motor vibration, the electromagnetic force, was analyzed analytically. At the same time, the main factor causing motor vibration, the radial electromagnetic force, and the vibration noise characteristics under different working conditions and speeds were simulated using finite element analysis. The source and spatial order distribution of the electromagnetic force and the vibration noise characteristics under multiple speeds were analyzed. Next, a response surface modeling (RSM) model, to solve the specific analytical relationship between the design variables and the optimization objectives, and to perform multi-objective optimization design of the motor by combining the Taguchi method improved by fuzzy theory. Then, a sensitivity analysis of each design variable is performed based on the Pearson coefficient, and different methods are used to perform secondary parameter adjustment for design variables with different sensitivities. Finally, motor performance (output torque, torque ripple, air- gap flux density, vibration, noise) is compared pre- and post-optimization in both traditional Taguchi and the improved Taguchi-based schemes. This validation confirms the rationality and effectiveness of the proposed optimization methodology.