Research on Multi-objective Optimization of Vehicle Compatibility of Automobile Exhaust Thermoelectric Generator Systems

被引：0
作者：
Quan R. [1 ,2 ]
Li T. [1 ,2 ]
Yue Y. [1 ,2 ]
Chang Y. [1 ,2 ]
Tan B. [3 ]
机构：
[1] Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan
[2] Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan
[3] School of Science, Hubei University of Technology, Wuhan
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2022年 / 33卷 / 16期
关键词：
automobile exhaust thermoelectric generation; heat exchanger; multi-target grey wolf optimization algorithm; vehicle compatibility;
D O I：
10.3969/j.issn.1004-132X.2022.16.014
中图分类号：
学科分类号：
摘要：
When the automobile exhaust thermoelectric generator system was connected to the exhaust pipe of the engine, the airflow would be changed. In order to minimize the impacts on the original performance of the engines and improve the electrical power generation performance of the automobile exhaust thermoelectric generator systems, a hexagonal heat exchanger used for an automobile exhaust thermoelectric generator system was optimized for the on-board compatibility with the goal of the highest average surface temperature and the smallest pressure loss. A finite element simulation model of the heat exchanger was built based on CFD software to study the influences of the inlet gas speed of the heat exchanger on the surface temperature and pressure loss, as well as the influences of the inlet gas temperature on the surface temperature. The fins length, fins angle, fins width and fins spacing were taken as the design variables. The Gaussian process regression proxy model was established based on the test data, and the grey wolf algorithm was used to obtain the optimal solution in the multi-objective optimization function space. The results show that compared with the classical NSGA-Ⅱ algorithm, the Pareto solution set obtained by multi-objective grey wolf algorithm is more concentrated and the evaluation index is higher. The optimized heat exchanger with multi-objective grey wolf algorithm has a lower surface average temperature than that of several structures before optimization, but the pressure loss is significantly reduced. Compared with the cavity structure heat exchanger, the surface average temperature and pressure loss of optimized heat exchanger increase, and the pressure loss increasing amplitudes are within the acceptable ranges. The optimized heat exchanger may effectively take into account the power generation of the automobile exhaust thermoelectric generator systems and the on-board compatibility. © 2022 China Mechanical Engineering Magazine Office. All rights reserved.
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页码：2000 / 2007and2015
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