Development and experiment validation of variable-resistance-variable-capacitance dynamic simplified thermal models for shape-stabilized phase change material slab. (5th January 2019)

• Record Type: Journal Article
• Authors: Gao, Jiajia; Yan, Tian; Xu, Tao; Ling, Ziye; Wei, Gongda; Xu, Xinhua
• Is Part Of: Applied thermal engineering. Volume 146(2019)
• Page Start: 364
• Page End: 375
• Publication Date: 2019-01-05
• Subjects: Shape-stabilized phase change material (SSPCM) slab -- Variable-resistance-variable-capacitance model -- Thermal performance -- Parameter identification -- Experiment validation; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2018.09.124
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: The Variable-resistance-variable-capacitance simplified model for SSPCM slab were developed. Parameter identification of simplified models using GA was proposed. A SSPCM slab containing 80 wt% RT28 and 20 wt% EG is prepared. Thermal performances of the SSPCM slab were measured to validate the simplified models. Abstract: In recent years, shape-stabilized phase change material (SSPCM) slab arouses wide interests as a thermal storage media or thermal buffer in buildings for improving the thermal and energy performance. Traditional numerical models are widely used with low computational efficiency and low applicability of integration with conventional building thermal calculation package. Simplified model of SSPCM with good accuracy and high-efficiency is highly preferable for thermal performance prediction of building structures with SSPCM. This study presents variable-resistance-variable-capacitance simplified models with different orders (i.e., 2R1C, 4R2C and 6R3C model) for SSPCM slab. Parameters are identified using Genetic Algorithm. An experiment facility for measuring the dynamic thermal performance of SSPCM slab is established. The simplified PCM models are validated by comparing the model predictions and experiment measurements. Among these models, 4R2C model is more preferable since the parameters to be identified are less and the accuracy is also acceptable. The average error of surface temperature and heat flux are respectively 0.42 °C and 15%. The 4R2C model can represent the thermal dynamics of SSPCM with very simple structure. It can be easily integrated with conventional building simulation packages for thermal performance prediction of buildings with SSPCM as walls, roofs or ceilings etc.