Multi-parameter optimization analysis of permanent magnet couplings using response surface methodology and genetic algorithm

In this paper, the response surface methodology (RSM) and genetic algorithm (GA) are applied to the design optimization of permanent magnet couplings. The RSM offers notable advantages in efficiency and flexibility compared to traditional optimization methods, while the GA excels due to its global search capabilities and parallel processing features. The RSM and GA are used to optimize the experimental parameters, aiming to minimize the amount of permanent magnet material used in the permanent magnet coupling while ensuring magnetic torque. Optimization results demonstrate that, while ensuring the magnet torque of the coupling, the volume of the permanent magnet is reduced by 23.00 %, and the magnetic torque density is increased by 21.81 %. A reduction in the use of permanent magnet materials implies that the production costs of couplings can be substantially decreased. Therefore, the proposed method in this paper is a cost-effective solution for optimizing permanent magnet couplings.