Based on Filled Particle Swarm Optimization Algorithm of the Double-Secondary Permanent Magnent Synchronous Linear Motor Optimization Design

Abstract

Abstract:

This article proposes a filled particle swarm optimization(FPSO) algorithm to study the double-secondary permanent magnent synchronous linear motor optimization design. This article uses support vector machine to build the model of structure parameters and output performances on the foundation of FEM analysis. The technology of filled functions was introduced to improve the traditional particle swarm optimization algorithm, the test function proves that the FPSO can be more frequent and accurate in global optimization. Finally FPSO is applied to optimize the linear motor model. The simulation experiment shows that the optimized PMLSM has an increased thrust, and smaller thrust ripple, low peak current, the motor can reach the goal of optimization design.

Key words: Double-secondary permanent magnent synchronous linear motor, support vector machine, filled functions, particle swarm, global optimition

CLC Number:

TM359.4

Song Juncai,Dong Fei,Zhao Jiwen,Li Le,Su Yunsheng. Based on Filled Particle Swarm Optimization Algorithm of the Double-Secondary Permanent Magnent Synchronous Linear Motor Optimization Design[J]. Journal of Electrical Engineering, 2015, 10(8): 56-61.

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参数	数值
永磁体长度l	36.15
永磁体宽度h	12.20
气隙δ	1.60
极距τ	18.35
线圈长度S	7.06

电机结构参数					输出性能参数
l	h	δ	τ	S	η(%)	F	I
36	13	1.85	18.8	6.8	1.207	35.2	3.574
36	14	1.95	18.9	6.8	0.834	36.7	3.684
37	16	2.15	19.1	7.0	0.956	37.8	3.412
38	15	2.00	19.0	7.1	0.672	36.2	3.689
…	…	…	…	…	…	…	…
…	…	…	…	…	…	…	…
46	18	2.1	19.3	7.3	2.036	37.5	3.889

电机结构参数
	l	h	δ	τ	S
优化前	36.21	13.26	1.85	18.46	3.15
优化后	38.26	14.57	2.12	18.84	3.04

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