基于黑洞多目标进化算法的永磁直线同步电机优化设计研究
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中国地质大学(武汉)

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Optimization of a Tubular Coreless Linear PM Synchronous Machine Based on Multiobjective
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Affiliation:

China University Of Geosciences,wuhan

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    本文应用了一种改进的黑洞多目标进化算法(Multi-Objective Black-Hole),实现了对圆筒型无槽无铁芯直线永磁同步电机(Linear Permanent Magnet Synchronous Machine)的多目标优化设计,黑洞进化算法在不同Pareto区域的收敛速度、种群多样性、种群收敛性和亚种群获取等方面具有良好的性能.本文在分析无槽无铁芯圆筒直线电机的电磁解析模型和MOBH算法基础上,建立电机推力、推力体积比、铜损(效率)多目标优化模型.与三个目标对应的Pareto占优解空间提供更加全面和直观的最优解空间.可以根据应用需求和目标函数实际物理值分布范围来综合选取最终最优解,探讨了单一目标函数情况下Pareto占优解分布与主要设计变量的关系.最后通过样机实验验证主要设计指标的计算的准确性.

    Abstract:

    In this paper, a new multi-objective black-hole(MOBH) evolutionary algorithm is applied to optimization of a tubular linear permanent magnet synchronous motor(LPMSM). MOBH has good performance in convergence rate, population diversity, population convergence and subspecies acquisition in different Pareto regions. Based on the motor model and introduction of the MOBH algorithm, a multi-objective optimization model regarding to thrust, ratio between thrust and volume and copper loss(efficiency) is established. The Pareto dominated solution space corresponding to the three objectives provides a more comprehensive and intuitive optimal solution space. The final optimal solution can be comprehensively selected according to the application requirements and the actual physical value distribution range. The relationship between the distribution of Pareto dominant solutions and the main design variables under a single objective condition is discussed. Finally, the accuracy of the calculation of the main design indexes is verified by the prototype experiment.

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历史
  • 收稿日期:2020-06-30
  • 最后修改日期:2021-03-30
  • 录用日期:2021-04-07
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