Kong Xiaoguang, Yang Zhuo
School of Information Engineering, Shenyang University of Chemical Technology, Shenyang, China.
Sci Rep. 2025 Jul 2;15(1):22982. doi: 10.1038/s41598-025-07655-6.
Dual-stator permanent magnet motors (DSPMMs) have the advantages of fast control response, high torque density, and strong overload capacity, and thus are widely used in CNC machine tools, heavy mining machinery, oil drilling machinery, large industrial conveyor belts and lifting equipment and other fields. In this paper, taking a dual-stator permanent magnet motor as an example, the multi-variable combination scanning (MVCS) method is proposed to optimize the outside air-gap length and the slot width of the external unit motor to effectively weaken the cogging torque for the problem of large cogging torque. Furthermore, under temperature and stress constraints, in order to enhance the average torque and reduce the torque ripple, firstly, the magnetic bridge height, magnetically conductive layer thickness, inside air-gap length, and the top and bottom air barrier width of the internal unit motor are analyzed for sensitivity. Then, the Taguchi method optimizes the significant variables, the genetic algorithm based on the Kriging response surface model optimizes the non-significant variables, and finally, the optimal solution is selected on the Pareto front. The simulation results show that the performance targets of the motor are significantly improved after optimization, thereby verifying the effectiveness of the proposed methods.
双定子永磁电机（DSPMMs）具有控制响应快、转矩密度高、过载能力强等优点，因此广泛应用于数控机床、重型矿山机械、石油钻井机械、大型工业输送带及起重设备等领域。本文以双定子永磁电机为例，针对齿槽转矩较大的问题，提出多变量组合扫描（MVCS）方法对外部单元电机的外气隙长度和槽宽进行优化，以有效削弱齿槽转矩。此外，在温度和应力约束条件下，为提高平均转矩并降低转矩脉动，首先对内部单元电机的磁桥高度、导磁层厚度、内气隙长度以及顶部和底部气障宽度进行敏感性分析。然后，采用田口方法对显著变量进行优化，基于克里金响应面模型的遗传算法对非显著变量进行优化，最后在帕累托前沿上选择最优解。仿真结果表明，优化后电机的性能指标得到显著提高，从而验证了所提方法的有效性。
