基于改进遗传算法的汽车散热器优化设计  

Optimal design of automotive radiator based on modified genetic algorithm

作　　者：唐爱坤[1] 潘剑锋[1] 陈春伟[1] 李德桃[1] 于海群[1] 

机构地区：[1]江苏大学能源与动力工程学院,江苏镇江212013

出　　处：《江苏大学学报（自然科学版）》2008年第5期424-427,共4页Journal of Jiangsu University：Natural Science Edition

基　　金：江苏省自然科学基金资助项目(BK2003048);江苏省"青蓝工程"资助项目

摘　　要：根据汽车散热器体积小、耗材少的设计要求,提出了相应的优化目标函数;选定散热器百叶窗翅片的波高、波距、水管横截面长、宽、芯体总宽等结构参数作为决策变量,采用遗传算法对其进行结构优化计算;通过对换热器遗传算法优化过程特点的研究,对基本遗传算法的种群初始化、选择算子、变异算子等作了一定的改进;为验证优化模型和改进遗传算法的正确性,编制了优化设计软件,优化实例显示优化后的散热器的换热面积比原型减少了31.2%,表明改进后的遗传算法用于汽车散热器的结构优化,能够取得较好的优化效果.According to the design requirement of decreasing the volume and material uses, corresponding object function was established. Genetic algorithm was used to optimize the structure of radiator, including the wave hight and distance of the corrugated fin, length and width of the water pipe cross section, and core width as the decision variables. By studying the characteristics of optimization course, population initialization, selection operator and mutation operator of simple genetic algorithms were modified. Optimal design software was developed so as to verify the correctness of optimal model and modified genetic algorithms. Optimal example showed that the heat transfer area was reduced by 31.2% after optimization. So this modified method can obtain a better optimal effect on the radiator structure optimization.

关 键 词：汽车散热器 改进遗传算法 优化设计 结构参数 

分 类 号：TQ028.61[化学工程] O224[理学—运筹学与控制论]