Dynamic modeling of airflow rate through window openings based on CO2 data

Abstract

Better estimation of air change rate in naturally ventilated buildings is a key for supporting passive summer thermal comfort strategies. In window aired configurations, this estimation is challenging either with measurements or building simulation methods. In this study, we describe and apply the state space modeling methodology based on the carbon dioxide concentration (CO2) mass balance equation to a simple test case with numerically generated data. We show that a two-state CO2 / Air Change Rate model is suitable. As a modeling novelty, we demonstrate the benefit of improving the formulation with a variable diffusion term for the air change rate state equation. From the test case study findings, we emphasize that a lower interior-exterior CO2 difference results in weaker performance and we list some prospects for future work.