重庆理工大学学报2026，Vol.40Issue(5)：222-229,8.DOI:10.3969/j.issn.1674-8425(z).2026.03.027
热电制冷除湿模组输入参数多目标优化研究
Multi-objective optimization study of input parameters for thermoelectric cooling dehumidification module
摘要
Abstract
The overall performance of thermoelectric cooling dehumidification modules is affected by input parameters of the integrated thermoelectric system.To optimize module performance,this paper proposes a hybrid optimization strategy combining response surface methodology(RSM)with the multi-objective genetic algorithm(NSGA-Ⅱ).First,a condensation simulation model is built to investigate the effects of thermoelectric current(I),cold-side airflow rate(v1),and hot-side airflow rate(v2)on dehumidification capacity(E)and energy efficiency ratio(η).Then,RSM-based fitting equations for E and ηas functions of input parameters are built.Finally,utilizing these equations as fitness functions,the NSGA-Ⅱalgorithm achieves collaborative optimization of E and η.This strategy may provide some insights into the applications and optimized design of thermoelectric dehumidification modules.关键词
热电制冷/性能优化/响应面法/遗传算法Key words
thermoelectric dehumidification/performance optimization/response surface methodology/genetic algorithm分类
通用工业技术引用本文复制引用
赵华东,王华兴,付吉亮,李晨阳,张景双,铁瑛..热电制冷除湿模组输入参数多目标优化研究[J].重庆理工大学学报,2026,40(5):222-229,8.基金项目
郑州市协同创新重大专项(18XTZX12005) （18XTZX12005）
