Estimation of a room ventilation air change rate using a stochastic grey-box modelling approach. (August 2018)

• Record Type: Journal Article
• Authors: Macarulla, Marcel; Casals, Miquel; Forcada, Núria; Gangolells, Marta; Giretti, Alberto
• Is Part Of: Measurement. Volume 124(2018)
• Page Start: 539
• Page End: 548
• Publication Date: 2018-08
• Subjects: Indoor air quality -- Ventilation -- Air change rate estimation -- Stochastic methods -- Low-order model; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2018.04.029
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: The grey-box modelling approach is used to estimate the room ventilation air change rate. Four days are enough to obtain suitable parametrization with grey-box modelling. The CO2 sensor location is not important when the grey-box modelling approach is used. Abstract: The measurement of ventilation air change rate is a difficult, expensive task in buildings. Usually, the tracer-gas mass balance equation is used to determine ventilation air change rates. This method uses an ordinary differential equation. Consequently, it cannot deal with disturbances that enter the system, such as the influence of unrecognized and unmodelled inputs or the measurement noise. The use of the stochastic grey-box modelling approach, which is less common in the ventilation field, can help to deal with disturbances that can affect the system. The objective of this paper is to assess the potential of using the stochastic grey-box modelling approach to estimate the ventilation air change rate. The modelling is based on the stochastic differential equation of tracer-gas mass balance. The results show that this approach produces robust estimations to determine the ventilation air change rate of a room.