Approach on prediction of indoor temperature distribution by combining POD, CRI and mobile sensors

Abstract

In our previous study, a prediction method of indoor temperature distribution based on the Contribution Ratio of Indoor Climate (CRI) and finite air temperature collected by one mobile sensor has been proposed. However, the CRI fixed value hypothesis limits its application in practical situations. In this regard, this study proposes to introduce interpolation POD (proper orthogonal decomposition) method to obtain the dynamic distribution of CRI, so as to improve the prediction accuracy. As a case study, in a simplified CFD model with identified heat source conditions, based on the interpolation POD method, the reconstruction of each sub temperature field dominated by only one heat source under any air supply parameters was realized, and thus its CRI distribution could be calculated. Then, by combining the finite air temperature collected by the mobile sensor, the indoor temperature distribution was predicted. The results showed that the introduction of interpolation POD method is effective, which breaks the application limitations of CRI fixed value hypothesis on the proposed method, and further promotes its development potential in the direction of "real-time prediction and dynamic regulation" in practical application.