Parameter estimation of resistor-capacitor models for building thermal dynamics using the unscented Kalman filter

Simple item page
dc.coverageDOI: 10.1016/j.jobe.2020.101639
dc.creatorChen, Yuxiang
dc.creatorCastiglione, Juan
dc.creatorAstroza, Rodrigo
dc.creatorLi, Yong
dc.date2021
dc.date.accessioned2025-11-18T19:40:30Z
dc.date.available2025-11-18T19:40:30Z
dc.description<p>Accurate and computationally efficient building energy models are critical to the development of online or pseudo-online control strategies and other building management activities. However, such models need to overcome the large uncertainty involved with continuously changing occupant activities and building status. The present study uses unscented Kalman filtering (UKF) in the model parameter estimation for simple yet accurate resistor-capacitor (RC) models to develop reliable building energy models. The estimation procedure, mathematical operations, and other estimation enhancing techniques are presented in detail. Synthetic and measured data were used to validate and evaluate the methodology. The obtained model shows better performance when compared with a model that was calibrated using genetic algorithms in a previous study. This remarkable model performance shows that UKF can enable timely online model update and improve the model predictability.</p>eng
dc.identifierhttps://investigadores.uandes.cl/en/publications/fd0ce1d8-2c25-4b98-a9a4-cdb2729fc37f
dc.identifier.urihttps://repositorio.uandes.cl/handle/uandes/51317
dc.languageeng
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourcevol.34 (2021) date: 2021-02-01
dc.subjectBuilding energy models
dc.subjectParameter estimation
dc.subjectRC models
dc.subjectUnscented Kalman filter
dc.titleParameter estimation of resistor-capacitor models for building thermal dynamics using the unscented Kalman filtereng
dc.typeArticleeng
dc.typeArtículospa
Files
Collections
PURE