Identification of vapour compression air conditioning system behaviour using Bayesian regularization neural network

研究成果: Conference contribution

抄録

Identification for system dynamic behaviour is necessary to develop control strategy. In this paper, the dynamic performance of air conditioning (AC) system is predicted using artificial neural network (ANN) approach. The ANN is developed to predict exergy efficiency, coefficient of performance (COP), and cooling capacity. The controllable parameters including compressor speed and evaporator and condenser fan speed are considered as the input. The datasets for prediction are generated by AC system simulator. The system was simulated by randomly varying compressor speed and evaporator and condenser fan speed with N-sample signal input. The dynamic ANN configuration with Bayesian regularization is proposed to predict one-step ahead of system performance behaviour. The results show that the developed ANN in present study yields good prediction accuracy for all outputs. Accordingly, ANN can be further applied for predictive control application in AC system to control cooling capacity while maintaining system efficiency.

本文言語English
ホスト出版物のタイトルICR 2019 - 25th IIR International Congress of Refrigeration
編集者Vasile Minea
出版社International Institute of Refrigeration
ページ4061-4068
ページ数8
ISBN(電子版)9782362150357
DOI
出版ステータスPublished - 2019
イベント25th IIR International Congress of Refrigeration, ICR 2019 - Montreal, Canada
継続期間: 2019 8 242019 8 30

出版物シリーズ

名前Refrigeration Science and Technology
2019-August
ISSN(印刷版)0151-1637

Conference

Conference25th IIR International Congress of Refrigeration, ICR 2019
CountryCanada
CityMontreal
Period19/8/2419/8/30

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Condensed Matter Physics

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