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

Sholahudin, Keisuke Ohno, Seiichi Yamaguchi, Kiyoshi Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationICR 2019 - 25th IIR International Congress of Refrigeration
EditorsVasile Minea
PublisherInternational Institute of Refrigeration
Pages4061-4068
Number of pages8
ISBN (Electronic)9782362150357
DOIs
Publication statusPublished - 2019
Event25th IIR International Congress of Refrigeration, ICR 2019 - Montreal, Canada
Duration: 2019 Aug 242019 Aug 30

Publication series

NameRefrigeration Science and Technology
Volume2019-August
ISSN (Print)0151-1637

Conference

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

Keywords

  • Air Conditioning
  • Exergy
  • Neural Network
  • System Identification

ASJC Scopus subject areas

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

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  • Cite this

    Sholahudin, Ohno, K., Yamaguchi, S., & Saito, K. (2019). Identification of vapour compression air conditioning system behaviour using Bayesian regularization neural network. In V. Minea (Ed.), ICR 2019 - 25th IIR International Congress of Refrigeration (pp. 4061-4068). [1244] (Refrigeration Science and Technology; Vol. 2019-August). International Institute of Refrigeration. https://doi.org/10.18462/iir.icr.2019.1244