A Multi-Objective Optimization for Composite Leaf Springs Using Genetic Algorithms

doi:10.7652/xjtuxb201508017

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A Multi-Objective Optimization for Composite Leaf Springs Using Genetic Algorithms

更新时间：2025-07-09

- A Multi-Objective Optimization for Composite Leaf Springs Using Genetic Algorithms
- Vol. 49, Issue 8, Pages: 102-108(2015)
- 作者机构：
  
  吉林大学汽车仿真与控制国家重点实验室,长春,130022
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201508017
  CLC： U463.33+4.6
- Online First：10 August 2015，
  
  Published：2015
- 稿件说明：
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A Multi-Objective Optimization for Composite Leaf Springs Using Genetic Algorithms[J]. 2015, 49(8): 102-108.
DOI：

A Multi-Objective Optimization for Composite Leaf Springs Using Genetic Algorithms[J]. 2015, 49(8): 102-108. DOI： 10.7652/xjtuxb201508017.

摘要

为了使某客车复合材料板簧的性能达到最优

提出了一种针对复合材料板簧的多目标优化方法。综合应用遗传算法中的权重系数变换法和混合法

调用编写的复合材料板簧各项性能的Matlab计算程序

采用Matlab遗传算法工具箱建立了以铺层参数为设计变量

以复合材料板簧的刚度、强度和质量为子目标的多目标优化模型。优化结果表明

簧身的宽度应取最大值

从长度渐变铺层区域末端到中部凸起结构的簧身厚度应以抛物线规律增加。对优化得到的设计方案进行样件试制和台架试验。试验结果表明

优化得到的复合材料板簧质量为钢板弹簧的40%

疲劳寿命是钢板弹簧的3倍

同时也满足整车对板簧刚度和强度的要求。

Abstract

A multi-objective optimization method for the composite leaf spring of a type of buses is described to optimize the performance of the composite leaf spring. A multi-objective optimization model is established in the genetic algorithm toolbox of Matlab software by using the weighting coefficient transformation method and the hybrid method in genetic algorithms. The variables of the model are parameters of the layer scheme and the stiffness

the strength ratio and the mass of the composite leaf spring are sub-goals of the model. A Matlab program is coded to calculate the performance of the composite leaf spring. The results show that the width of the composite leaf spring should be maximized and the thickness of the composite leaf spring parabolically increases from the end of the layer region with gradient length towards the bump structure. The prototypes of the optimal design scheme are manufactured and a bench test is performed. The test results show that the mass and the fatigue life of the composite leaf spring are 40% and three times of those of the steel leaf spring

respectively. Moreover

the stiffness and the strength of the composite leaf spring also meet the requirements of this type of buses.

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references

吴辉, 李再轲, 姜其斌. 复合材料板式弹簧的研制及性能 [J]. 塑料工业, 2012, 40(8): 103-106.

WU Hui, LI Zaike, JIANG Qibin. Development and characteristics of composite's leaf spring [J]. China Plastics Industry, 2012, 40(8): 103-106.

SUBRAMANIAN C, SENTHILVELAN S. Short-term flexural creep behavior and model analysis of a glass-fiber-reinforced thermoplastic composite leaf spring [J]. Journal of Applied Polymer Science, 2011, 120(6): 3679-3686.

RAJENDRAN I, VIJAYARANGAN S. Design, analysis, fabrication and testing of a composite leaf spring [J]. Mechanical Engineering Division, 2002, 82(3): 180-187.

SHOKRIEH M M, REZAEI D. Analysis and optimization of a composite leaf spring [J]. Composite Structures, 2003, 60(3): 317-325.

RAJENDRAN I, VIJAYARANGAN S. Optimal design of a composite leaf spring using genetic algorithms [J]. Computers Structures, 2001, 79(11): 1121-1129.

KUMAR M S, VIJAYARANGAN S. Analytical and experimental studies on fatigue life prediction of steel and composites multi-leaf spring for light passenger vehicles using life data analysis [J]. Materials Science, 2007, 13(2): 141-146.

SUBRAMANIAN C, SENTHILVELAN S. Joint performance of the glass fiber reinforced polypropylene leaf spring [J]. Composite Structures, 2011, 93(2): 759-766.

王耀先. 复合材料力学与结构设计 [M]. 上海: 华东理工大学出版社, 2012: 50-67.

FERREIRA J A M, COSTA J D M, REIS P N B. Static and fatigue behavior of glass-fibre-reinforced polypropylene composites [J]. Theoretical and Applied Fracture Mechanics, 1999, 31(1): 67-74.

KUEH J J, FARIS T. Finite element analysis on the static and fatigue characteristics of composite multi-leaf spring [J]. Journal of Zhejiang University: A Science, 2012, 13(3): 159-164.

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