MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM

ZHANG YongLiang; CHEN Xu; YAO JiaSheng; ZHANG ShuaiShuai

doi:10.16579/j.issn.1001.9669.2021.03.015

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MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM

更新时间：2022-09-22

- MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM
- Journal of Mechanical Strength Vol. 43, Issue 3, Pages: 608-614(2021)
- 作者机构：
  
  1. 上海理工大学机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2021.03.015
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ZHANG YongLiang, CHEN Xu, YAO JiaSheng, et al. MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM. [J]. 43(3):608-614(2021)
DOI：

ZHANG YongLiang, CHEN Xu, YAO JiaSheng, et al. MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM. [J]. 43(3):608-614(2021) DOI： 10.16579/j.issn.1001.9669.2021.03.015.

摘要

为提升电机装配质量,降低总成本,需对形成电机定、转子间气隙的关键零部件组成环公差进行优化设计。以加工成本和质量损失成本为目标函数,以各关键组成环的公差值为设计变量,以装配功能和经济加工能力为约束条件,建立了多目标多约束的电机装配径向公差优化数学模型。基于改进的遗传算法对模型进行求解,得到电机总成本最低时的各关键组成环公差。通过Cetol 6σ仿真验证,结果表明:采用优化后的设计公差值,电机装配合格率提升了约55.7%,总成本下降了约45.2%。

Abstract

In order to improve the assembly quality of the motor and reduce the total cost,it is necessary to optimize the design of the tolerances of the key components that form the air gap between the motor stator and the rotor. A multi-objective and multi-constrained mathematical model for radial tolerance optimization of a motor assembly was established with processing cost and mass loss cost as objective functions,tolerance values of key components as design variables,and assembly functions and economic processing capabilities as constraints. The model was solved based on the improved genetic algorithm,and the key component tolerances under the lowest total were obtained. Through CETOL 6σ simulation verification,the results show that the passing rate of motor assembly is increased by about 55. 7%,and the total cost is reduced by about 45. 2% with the optimized design tolerance.

关键词

公差多目标优化遗传算法电机装配优化模型

Keywords

ToleranceMulti-objective optimizationGenetic algorithmMotor assemblyOptimization model

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