Prediction of compressor electric power based on gray relational mechanism combination model
In order to accurately obtain the compressor electric power,the GRM(1,m)-Mechanism combination prediction model was established using Matlab language through the experimental bench for the variable frequency rolling rotor refrigeration system according to the characteristics of the(GRM(1,m))prediction model such as low sample demand for gray correlation,high prediction accuracy and its ability to reflect the system essential characteristics.The compressor electric power was predicted by these three models respectively.The results show that the GRM(1,m)-Mechanism combination prediction model has better prediction accuracy and applicability than two other models.Its maximum relative error and average relative error were 4.05%and 1.71%respectively,which were 1.29%and 1.09%lower than that of the Mechanism model,and 1.02%and 2.19%lower than that of the gray correlation(GRM(1,m))prediction model.Finally,the average relative error of combination prediction model was verified to be within 1.9%by the compressor variable speed experiments,which further proved the accuracy and applicability of the GRM(1,m)-Mechanism model.
variable frequency rolling rotorelectrical powergray relationalmechanismprediction
国家科技期刊平台
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