Optimal selection of compressor models for minimum experimental data requirements
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.
国家科技期刊平台
NSTL
万方数据
