Intelligent prediction on performance of high-temperature heat pump systems using different refrigerants

作     者：YU Xiao-hui ZHANG Yu-feng ZHANG Yan HE Zhong-lu DONG Sheng-ming MA Xue-lian YAO Sheng 于晓慧;张于峰;张彦;贺中禄;董胜明;马学莲;姚胜

作者机构：School of Environmental Science and Engineering Tianjin University School of Architecture Tianjin University 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2018年第25卷第11期

页      面：2754-2765页

核心收录：

学科分类：08[工学] 081404[工学-供热、供燃气、通风及空调工程] 0814[工学-土木工程] 

基　　金：Project (2015CB251403) supported by the National Key Basic Research Program of China(973) 

主　　题：high-temperature heat pump experimental performance support vector machine back propagation neural network performance prediction 

摘      要：Two new binary near-azeotropic mixtures named M1 and M2 were developed as the refrigerants of the high-temperature heat pump(HTHP).The experimental research was used to analyze and compare the performance of M1 and M2-based in the HTHP in different running *** results demonstrated the feasibility and reliability of M1 and M2 as new high-temperature ***,the exploration and analyses of the support vector machine(SVM)and back propagation(BP)neural network models were made to find a practical way to predict the performance of HTHP *** results showed that SVM-Linear,SVM-RBF and BP models shared the similar ability to predict the heat capacity and power input with high ***-RBF demonstrated better stability for coefficient of performance ***,the proposed SVM model was used to assess the potential of the M1 and *** results indicated that the HTHP system using M1 could produce heat at the temperature of 130°C with good performance.