| Issue |
E3S Web Conf.
Volume 720, 2026
2026 11th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2026)
|
|
|---|---|---|
| Article Number | 05001 | |
| Number of page(s) | 8 | |
| Section | Building Energy Efficiency and Climate-Adaptive Technologies | |
| DOI | https://doi.org/10.1051/e3sconf/202672005001 | |
| Published online | 01 July 2026 | |
A system identification of radiant ceiling panels using simplified RC network model for cooling performance prediction under tropical climate in Thailand
1 The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
2 Department of Mechanical Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Accurate thermal modeling is essential for energy-efficient operation of building cooling systems, particularly in tropical climates where buildings are predominantly cooling-dominated. This study develops a gray-box thermal model for radiant cooling using a Resistance–Capacitance (RC) network with Dynamic Mode Decomposition (DMD) for automated parameter identification. Experiments were conducted in a 27 m² test chamber at King Mongkut’s University of Technology Thonburi (KMUTT) in Bangkok, Thailand, during the peak hot season, with outdoor temperatures reaching 35°C and solar radiation up to 1,390 W/m². A four-state RC model representing ceiling panel, indoor air, interior surface, and operative temperatures was developed. Using one week of data at 1-minute intervals, the model achieved 0.34°C RMSE in operative temperature prediction. Identified parameters showed physical consistency, with air time constants of 15–30min and surface time constants of 4–6h. Parameter identification required less than 5s, and forward prediction required less than 0.001s per step, supporting real-time applications. The method combines physical interpretability with computational efficiency, providing a practical tool for sustainable building energy management in tropical climates.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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