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Research on domestic air conditioners long-term performance and evaluation index.

Number: pap. n. 415

Author(s) : WU J., LIU C., LIANG Z., et al.

Summary

Performance of practical operation domestic air conditioner (AC) is an important evaluation index to estimate energy saving efficiency. In order to investigate characteristic of air conditioners long term performance (LTP) and to establish optimation design method of high LTP in multi-factors impact conditions, BP neural network prediction method has been applied. The training sample of LTP prediction BP neural network acquired form experimental result of practical operation domestic ACs and data of ACs dynamic LTP on-line monitor system. By a large size of training sample, the decision weights of multi-impact factors and LTP optimation strategies can be obtained. In order to establish a LTP prediction model, the performances of 26 practical operations domestic ACs have been tested. And the high temperature cooling condition performance, rated cooling condition performance, low temperature heating condition performance, rated heating condition performance of 26 samples has been obtained. 85% of testing sample results was served as training sample data and 15% of testing data was served as validation data to LTP prediction BP neural network. The result indicated that the prediction of LTP prediction BP neural network is convergence and error is less than 5% during the BP neural network training by 22 samples. The decision weights of time weighted high temperature cooling, rated cooling, low temperature heating, rated heating normalized performance value are 0.187, 0.203, 0.312, 0.298, respectively. For further increasing the prediction precision, practical operation domestic AC performance online monitor system and LTP online data acquisition website has been established for data acquisition to validate LTP prediction BP neural network.

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Pages: 8 p.

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Details

  • Original title: Research on domestic air conditioners long-term performance and evaluation index.
  • Record ID : 30015821
  • Languages: English
  • Source: Proceedings of the 24th IIR International Congress of Refrigeration: Yokohama, Japan, August 16-22, 2015.
  • Publication date: 2015/08/16
  • DOI: http://dx.doi.org/10.18462/iir.icr.2015.0415

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