An inverse hygrothermal model for multi-zone buildings

The dynamic hygrothermal behaviour of existing buildings can be characterized using data-driven models that are established via system identification techniques. However, most of the time the identification problem is difficult to solve for multi-zone buildings due to high dimensionality of the model and poor excitation in the training data. In addition, building thermal and moisture dynamics are coupled and simultaneous identification of the coupled model is challenging. This paper presents a simplified one-way coupled inverse model to capture the building thermal and moisture dynamics where the impact of space moisture on the building thermal response is neglected. This simplification enables the thermal and moisture sub-models to be estimated sequentially which reduces the computation complexity and improves model identifiability. Both thermal and moisture sub-models adopt a physically based approach in which moisture interactions between different zones are neglected while the inter-zonal thermal interactions are captured. A 3-step procedure is developed to reduce the problem dimension in identifying the thermal sub-model. As a case study, the overall approach was applied to model a medium-size commercial building with nine thermal zones from measured data and the estimated models were validated for different periods of time during a cooling season.