摘要
为改善磁悬浮飞轮电机的悬浮和转矩性能,提出了一种单绕组磁悬浮开关磁阻电机(single winding bearingless switched reluctance machine,SWBSRM)结构优化设计方法。通过有限元分析,结合响应面法与遗传粒子群算法对电机结构参数作进一步优化。首先通过中心复合试验设计建立样本数据空间,建立电机平均悬浮力和转矩的响应面模型。并以提高转矩和悬浮输出为优化目标,采用遗传粒子群算法获取最优参数组合。有限元仿真结果表明,优化后的电机平均转矩和平均悬浮力分别提高了22.81%和141.04%,验证了基于响应面法和遗传粒子群算法的SWBSRM结构多目标优化设计的有效性。
In order to improve the levitation and torque performance of the magnetic levitation flywheel motor,a structural optimization design method for a single-winding magnetic levitation switched reluctance motor(single winding bearingless switched reluctance motor,SWBSRM)was proposed.This design idea is to further optimize the structure parameters of the motor through finite element analysis,combined with response surface method and genetic particle swarm optimization.Firstly,the sample data space is established through the central composite experimental design,and the response surface model of the average suspension force and torque of the motor is built.In order to improve the torque and suspension output as the optimization goal,the genetic particle swarm algorithm is used to obtain the optimal parameter combination.The finite element simulation results show that the optimized motor’s average torque and average suspension force are increased by 22.81%and 141.04%,respectively,which verifies the effectiveness of the multi-objective optimization design of SWBSRM structure based on response surface method and genetic particle swarm optimization.
作者
邵淋晶
朱海浪
张巍
Shao Linjing;Zhu Hailang;Zhang Wei(School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing Jiangsu 211167, China)
出处
《电气自动化》
2022年第1期3-6,共4页
Electrical Automation
关键词
飞轮储能
单绕组磁悬浮开关磁阻电机
响应面法
多目标优化
遗传粒子群算法
flywheel energy storage
single winding bearingless switched reluctance motor
response surface method
multi-objective optimization
genetic algorithm particle swarm optimization(GAPSO)
