CO2 based multizone demand-controlled ventilation
Ventilation systems which are part of Heating, Ventilating and Air Conditioning (HVAC) system must be designed and controlled properly, to reduce the amount of energy consumed by them without affecting the quality of air in a conditioned space. A new algorithm to control airflow rate in a multizo...
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sg-ntu-dr.10356-763362023-07-04T15:40:27Z CO2 based multizone demand-controlled ventilation Nandhini, Ramakrishnan Cai Wenjian School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Ventilation systems which are part of Heating, Ventilating and Air Conditioning (HVAC) system must be designed and controlled properly, to reduce the amount of energy consumed by them without affecting the quality of air in a conditioned space. A new algorithm to control airflow rate in a multizone Dedicated Outdoor Air System (DOAS) is proposed in this project to reduce the energy consumed by ventilation system in a building. A duct network of the HVAC system was modeled using Simscpae, a powerful MATLAB tool which enables creating models of physical systems and developing control systems within Simulink environment. Simscape was also used for analyzing performance of the designed system. The proposed algorithm obtained by cascading fuzzy-logic based feedforward control and PID-based feedback control, controls airflow rate in a conditioned space by monitoring carbon dioxide (CO2) during occupied hours and maintains a minimum flow to dilute contaminants released by Volatile Organic Compounds (VOC) inside a room, during unoccupied hours. Performance of the new control algorithm was verified and it was observed that the new algorithm achieves better performance than the standard PID control system, by maintaining CO2 levels at recommended standards and achieving thermal comfort. Master of Science (Computer Control and Automation) 2018-12-19T14:49:10Z 2018-12-19T14:49:10Z 2018 Thesis http://hdl.handle.net/10356/76336 en 54 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Nandhini, Ramakrishnan CO2 based multizone demand-controlled ventilation |
description |
Ventilation systems which are part of Heating, Ventilating and Air Conditioning
(HVAC) system must be designed and controlled properly, to reduce the amount of
energy consumed by them without affecting the quality of air in a conditioned space. A
new algorithm to control airflow rate in a multizone Dedicated Outdoor Air System
(DOAS) is proposed in this project to reduce the energy consumed by ventilation system
in a building. A duct network of the HVAC system was modeled using Simscpae, a
powerful MATLAB tool which enables creating models of physical systems and
developing control systems within Simulink environment. Simscape was also used for
analyzing performance of the designed system. The proposed algorithm obtained by
cascading fuzzy-logic based feedforward control and PID-based feedback control,
controls airflow rate in a conditioned space by monitoring carbon dioxide (CO2) during
occupied hours and maintains a minimum flow to dilute contaminants released by
Volatile Organic Compounds (VOC) inside a room, during unoccupied hours.
Performance of the new control algorithm was verified and it was observed that the new
algorithm achieves better performance than the standard PID control system, by
maintaining CO2 levels at recommended standards and achieving thermal comfort. |
author2 |
Cai Wenjian |
author_facet |
Cai Wenjian Nandhini, Ramakrishnan |
format |
Theses and Dissertations |
author |
Nandhini, Ramakrishnan |
author_sort |
Nandhini, Ramakrishnan |
title |
CO2 based multizone demand-controlled ventilation |
title_short |
CO2 based multizone demand-controlled ventilation |
title_full |
CO2 based multizone demand-controlled ventilation |
title_fullStr |
CO2 based multizone demand-controlled ventilation |
title_full_unstemmed |
CO2 based multizone demand-controlled ventilation |
title_sort |
co2 based multizone demand-controlled ventilation |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/76336 |
_version_ |
1772829036643352576 |