The primary objective of this paper is to develop a hybrid grey box model that integrates air and thermal dynamics to improve accuracy in both domains. The methodology involved developing four grey box models to estimate ventilation airflows using indoor CO2 concentration data and six thermal models to estimate thermal properties and heat gains using indoor temperature data. To ensure accurate parameterization, measurements of outdoor conditions, occupancy, and HVAC operations were incorporated. The results revealed that models treating infiltration and mechanical ventilation as mutually exclusive (IAQ-3 and IAQ-4) and those integrating ventilation heat gains from estimated airflows (T-6) performed most effectively. This hybrid approach underscores the benefits of incorporating ventilation heat loos or gains, based on airflow estimation derived from indoor air quality (IAQ) models, into thermal modelling, significantly improving accuracy and reducing parameter variability. The findings demonstrate the potential of this methodology for applications in ventilation management and HVAC optimization. By enhancing energy efficiency and improving indoor air quality, this approach supports the development of healthier, more sustainable indoor environments.

This research was supported by a predoctoral contract grant (reference no. PRE2021-099606) as part of the research and development project IAQ4EDU (reference no. PID2020-117366RB-I00), funded by MCIN/AEI/10.13039/501100011033/FEDER, and is part of the project BINAFET (reference no. TED2021-130047B-C22), funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR. Moreover, this study was supported by the Catalan agency AGAUR through its research group support programme (2021 SGR 00341).