Assessment of Different Approaches to Model the Thermal Behavior of a Passive Building via System Identification Process
BRUNEAU, Denis
École nationale supérieure d'architecture et du paysage de Bordeaux [ENSAP Bordeaux]
Institut de Mécanique et d'Ingénierie [I2M]
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École nationale supérieure d'architecture et du paysage de Bordeaux [ENSAP Bordeaux]
Institut de Mécanique et d'Ingénierie [I2M]
BRUNEAU, Denis
École nationale supérieure d'architecture et du paysage de Bordeaux [ENSAP Bordeaux]
Institut de Mécanique et d'Ingénierie [I2M]
< Reduce
École nationale supérieure d'architecture et du paysage de Bordeaux [ENSAP Bordeaux]
Institut de Mécanique et d'Ingénierie [I2M]
Language
EN
Communication dans un congrès
This item was published in
Advances in automation and robotics research : Proceedings of the 2nd latin american congress on automation and robotics, Cali, Colombia 2019, 2nd Latin American Congress on Automation and Robotics, 2019-10-30, Cali. 2020-01-30, vol. 409, p. 185-193
Springer International Publishing
English Abstract
A preliminary study is presented with the aim of modeling the thermal behavior of a passive building that is ventilated merely with the promotion of natural ventilation, various models have been assessed by using the system ...Read more >
A preliminary study is presented with the aim of modeling the thermal behavior of a passive building that is ventilated merely with the promotion of natural ventilation, various models have been assessed by using the system identification process. The identification of a simplify and lite model of such thermal behavior is needed to later control the thermal comfort of the indoor environment through the building natural ventilation openings and window blinds. A physical-phenomena-based model using electrical analogies is built upon hypotheses allowed by the architectural features of the building. This helps analyze the interaction between the main elements of the physical domain, where the thermal behavior is only determined by the indoor air and concrete-slab temperatures. Three model approaches are examined with the help of the system identification toolbox: State space, Process models (linear and frequency domain), and Nonlinear representation. The nonlinear representation model is the best fitted encountered after 13 iterations with an accuracy of 71%.Read less <