A systematic literature review on smart and personalized ventilation using CO&lt;sub&gt;2&lt;/sub&gt; concentration monitoring and control

Song, Ge; Ai, Zhengtao; Liu, Zhengxuan; Zhang, Guoqiang

doi:10.1016/j.egyr.2022.05.243

A systematic literature review on smart and personalized ventilation using CO₂ concentration monitoring and control

Title

A systematic literature review on smart and personalized ventilation using CO₂ concentration monitoring and control

Author

Song, Ge (Hunan University)
Ai, Zhengtao (Hunan University)
Liu, Zhengxuan (TU Delft Design & Construction Management; Hunan University)
Zhang, Guoqiang (Hunan University)

Date

2022

Abstract

Smart and personalized ventilation systems have been demonstrated with high performance in creating a healthy and energy-efficient indoor environment, but they have been rarely comprehensively summarized and explored in previous studies. With the progressive development of various terminal devices and control technologies, personalized ventilation based on intelligent control is potentially a promising way to achieve efficient control and energy savings in human micro-environments. This study comprehensively summarizes and analyzes the recent studies and common utilization forms of smart ventilation and PV systems that are based on CO₂ concentration control, to pave path and provide some guidelines for their integration application for reducing energy consumption and improving indoor thermal comfort. Research shows that the combination of personalized ventilation and smart ventilation is an essential development for ventilation systems. Smart ventilation with demand control logic based on CO₂ concentration has been mature enough to effectively improve the effectiveness and comfortable performance of personalized ventilation. However, switching from traditional air conditioning systems to personalized ventilation still requires improved sensors and intelligent control algorithms. In addition, this paper also summarizes the exploratory studies and potential application analysis of machine-learning theories to improve intelligent control of personalized ventilation. To this end, this paper identifies future tendencies for advanced theories, integrated systems, and devices in personalized ventilation systems.

Subject

CO concentration
Energy saving
Personalized ventilation
Smart control
Thermal comfort

To reference this document use:

http://resolver.tudelft.nl/uuid:4beb8f41-497d-4865-9140-2535f0eeef48

DOI

https://doi.org/10.1016/j.egyr.2022.05.243

ISSN

2352-4847

Source

Energy Reports, 8, 7523-7536

Part of collection

Institutional Repository