家电科技Issue(z1)：27-32,6.DOI:10.19784/j.cnki.issn1672-0172.2024.99.006
面向最小实验数据需求的压缩机模型优选
Optimal selection of compressor models for minimum experimental data requirements
翁晓敏 1王龙炎 2丁国良2
作者信息
- 1. 广东美的暖通设备有限公司 广东 佛山 528311
- 2. 上海交通大学机械与动力工程学院 上海 200240
- 折叠
摘要
Abstract
In addition to improving accuracy,the compressor model used in refrigeration system simulation also requires as few experimental samples as possible for model correction.Based on experimental test data,different models are compared.And the compressor model with the smallest experimental data requirement is selected from the models with relatively good accuracy.The results show that for mass flow rate,the reciprocal of the polytropic index is used to correct the pressure ratio term,and the pressure loss of the suction process is considered for characterisation;for input power,high and low pressure and high and low pressure cross terms are used for characterisation,which can meet the requirements of high accuracy and small data requirement at the same time.Only 5 sets of experimental data are required to accurately fit the undetermined coefficients in the compressor model,and the average errors of the model prediction of mass flow rate and input power are within 1.5％and 2％,respectively.关键词
压缩机/压缩机模型/十系数模型/数据需求量Key words
Compressor/Compressor model/Ten-coefficient model/Data requirement分类
信息技术与安全科学引用本文复制引用
翁晓敏,王龙炎,丁国良..面向最小实验数据需求的压缩机模型优选[J].家电科技,2024,(z1):27-32,6.
