Black Box Modelling and Simulating the Dynamic Indoor Air Temperature of a Laboratory Using the Continuous-Time Transfer Function Model

DOI

10.2991/aer.k.201229.021How to use a DOI?

Keywords

Modelling and simulation, black box modelling, building air temperature simulation, building air temperature prediction

Abstract

The air conditioner is one of the devices that uses a high amount of electricity – more electricity consumption means more heat and greenhouse gases emitted to the environment if the electricity is generated by fossil fuel sources such as coal, diesel, natural gas etc. Energy-efficient control algorithms and strategies can be proposed to reduce the power consumption without sacrificing thermal comfort – time and cost can be saved by developing and testing these control algorithms and strategies via computer simulation instead of developing and testing them on the actual site, but this requires the availability of the mathematical model representing the dynamic behaviour of the system that is desired to be simulated. In this research, a black box model representing the dynamic indoor air temperature behaviour of the Industrial Instrumentation Laboratory at Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia (UTM) Kuala Lumpur is developed based on the continuous-time transfer function model using the System Identification Toolbox™ in MATLAB® software to get a new model with a simpler model structure for a more practical simulation than the autoregressive–moving-average (ARMA) model developed in the previous research representing the same behaviour without sacrificing a significant level of accuracy. Both the continuous-time transfer function model and the ARMA model are developed based on the actual recorded data from the laboratory and minimal physical characteristics knowledge of the laboratory. The result shows that the optimised continuous-time transfer function model generated by the System Identification Toolbox™ in this research has a significantly simpler model structure than the optimised ARMA model developed in the previous research (standardised eight poles and two zeros for all inputs versus standardised past inputs and outputs for all inputs and output), and only slightly less accurate in terms of percentage of fitting, value ( and versus and for training and testing data set).

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shamsul Faisal Mohd Hussein
AU  - Noor Bazila Sharifmuddin
AU  - Mohd. Fitri Alif Mohd. Kasai
AU  - Abdulqader Omar Al-Rabeei
AU  - Amrul Faruq
AU  - Siti Munirah Zulkapli
AU  - Noorazizi Mohd Samsuddin
AU  - Sheikh Ahmad Zaki Shaikh Salim
AU  - Shahrum Shah Abdullah
PY  - 2020
DA  - 2020/12/30
TI  - Black Box Modelling and Simulating the Dynamic Indoor Air Temperature of a Laboratory Using the Continuous-Time Transfer Function Model
BT  - Proceedings of the Third International Conference on Separation Technology 2020 (ICoST 2020)
PB  - Atlantis Press
SP  - 146
EP  - 157
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201229.021
DO  - 10.2991/aer.k.201229.021
ID  - Hussein2020
ER  -