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基于遗传算法的温差发电系统模块布局优化设计
引用本文:冯一芒,孔德奎,毕世权,崔浩,张永存.基于遗传算法的温差发电系统模块布局优化设计[J].计算力学学报,2022,39(2):161-169.
作者姓名:冯一芒  孔德奎  毕世权  崔浩  张永存
作者单位:大连理工大学工业装备结构分析国家重点实验室,大连116024,沈阳飞机设计研究所,沈阳110035
基金项目:国家自然科学基金(11972105;U1808215;11821202);中央高校基本科研业务费专项资金资助项目.
摘    要:温差发电在航空航天等极端环境供电和汽车余热利用等领域具有重要的应用,然而低的热电转换效率严重限制了其发展.目前主要从提高材料本身性能和优化热电模块结构两方面提升性能.本文从整体出发,建立了基于遗传算法的温差发电系统模块布局优化设计方法.融合已有的解析模型,发展了能够快速获得系统电输出功率的性能评估方法;通过遗传算法,以...

关 键 词:温差发电  遗传算法  布局优化  热电模块
收稿时间:2021/1/22 0:00:00
修稿时间:2021/2/19 0:00:00

Optimization design of thermoelectric system module layout based on genetic algorithm
FENG Yi-mang,KONG De-kui,BI Shi-quan,CUI Hao,ZHANG Yong-cun.Optimization design of thermoelectric system module layout based on genetic algorithm[J].Chinese Journal of Computational Mechanics,2022,39(2):161-169.
Authors:FENG Yi-mang  KONG De-kui  BI Shi-quan  CUI Hao  ZHANG Yong-cun
Institution:State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China;Shenyang Aircraft Design & Research Institute, Shenyang 110035, China
Abstract:Thermoelectric generation has important potential applications such as power supply in extreme aerospace environment,waste heat utilization in automobile and others.However,their wide scale applications have been hindered due to low its thermal-to-electrical conversion efficiency.At present,the performance improvement is mainly made from two aspects: improving the material performance and optimizing the thermoelectric module structure.In this paper,a method of module layout optimization of a thermoelectric generator based on a genetic algorithm is proposed.By combining the existing analytical models,a performance evaluation method which can quickly obtain the electricity generation of the system is developed.Through the genetic algorithm,the thermal-to-electrical conversion of waste heat gas is taken as an example to realize the layout (number and location) design of the modules in the thermoelectric generator.The influence of waste heat gas flow velocity and temperature is discussed.Comparing with the fully covered thermoelectric module layout design,the optimized design achieves a higher electric power with fewer thermoelectric modules,which proves that including too many thermoelectric modules can have a negative effect,and that there is an optimal number and location of thermoelectric modules.This study provides a possible way to improve the electric output power in thermoelectric generation.
Keywords:thermoelectric generator  genetic algorithm  layout optimization  thermoelectric module
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