Concise Parameter Identification Method for 1C1R Gray-Box Model Using Thermal Balance Points Associated with Active Cooling/Heating. Issue 37 (2022)

• Record Type: Journal Article
• Authors: Takahashi, Atsushi; Hokari, Hiroaki; Doi, Mamoru; Yoshikawa, Nobuyuki; Mariyama, Toshisada; Ueda, Naonori
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 37(2022)
• Page Start: 463
• Page End: 468
• Publication Date: 2022
• Subjects: air conditioner -- gray-box model -- parameter estimation -- system identification; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.11.226
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Gray-box modeling of the thermal environment of buildings is widely used. The simplest gray-box model, called the 1C1R, is particularly important because it provides the first approximation of the thermal characteristics of building fabrics. We propose a fast and robust estimation method in which we introduce an integrated form of the 1C1R model as well as active cooling/heating at night to generate temperature change. The artificial temperature change is utilized to sequentially estimate the model parameters. Numerical experiments showed that our method is not only accurate but also avoids the multi-collinearity problem that conventional approaches have been suffering.