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J. Hefei Univ. Tech. (Nat. Sci.)

合肥工业大学学报(自然科学版)

JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY (NATURAL SCIENCE)

Competent Authorities: Ministry of Education of the People's Republic of China

Sponsor by: Hefei University of Technology

ISSN 1000-1646, CN 34-1001/N

Structural parameter optimization of electric scroll compressor based on genetic algorithm

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基于遗传算法的电动涡旋压缩机结构参数优化

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Dec.2024, Vol.47 No.12: 1617-1622

DOI: 10.3969/j.issn.1003-5060.2024.12.005

Authors

PAN Shuli, TANG Jingchun, SUN Dongfang, ZHOU Pei

(School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: In order to reduce the energy consumption in air conditioning system and improve the endurance capacity of electric vehicles, genetic algorithm is used to optimize the main structural parameters of the vortex disk of the electric scroll compressor. The flow of working medium in electric scroll compressor is calculated and analyzed by means of computational fluid dynamics (CFD). The results of simulation calculation and compressor performance experiment show that, under the same suction volume and operating conditions, by optimizing the relevant structural parameters of the vortex disk, the external compression indicated work is reduced by 60.71%, and the exhaust temperature of the center chamber is reduced by 1-2 K. The internal flow field analysis of the electric scroll compressor indicates that the vortex disk with optimized structure parameters can reduce the flow power consumption caused by the gas vortex to a certain extent, thus reducing the total power consumption of the electric scroll compressor. The experimental results show that the optimized input power decreases by 2.68% under the condition that the refrigerating capacity of the compressor remains unchanged.

Keywords: scroll compressor; genetic algorithm; flow field analysis; structure optimization

作者信息

潘淑丽，唐景春，孙东方，周培

（合肥工业大学汽车与交通工程学院，安徽合肥230009）

摘要和关键词

摘要: 为了降低电动汽车空调系统的耗能,提高电动汽车续航能力,文章使用遗传算法对电动压缩机涡旋盘的主要结构参数进行优化设计,并运用计算流体力学(computational fluid dynamics, CFD)方法对电动涡旋压缩机内部工质的流动进行计算和分析。仿真计算和压缩机性能试验结果表明,在相同的压缩机吸气容积和运行工况条件下,通过优化涡旋盘的相关结构参数,压缩机的外压缩指示功降低60.71%,压缩中心腔排气温度降低1~2 K;分析电动涡旋压缩机工作时的内部流场可知,结构参数优化后的涡旋盘在一定程度上减少了因气体涡流而导致的流动功耗,降低了电动涡旋压缩机的压缩总功耗,在压缩机制冷量不变的情况下,优化后输入电功率降幅为2.68%。

关键词: 涡旋压缩机；遗传算法；流场分析；结构优化

Funding

国家自然科学基金资助项目（52006051）

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