| dc.description.abstract | There is a significant potential for energy savings in cleanroom air conditioning or HVAC (Heating, Ventilation, and Air Conditioning) systems. Important components of these systems, insufflators, or fans, which recirculate clean air constantly and for this reason are assets that demand high energy costs. Several publications report that the airflow in cleanrooms is usually projected above the required value. At the same time, several published studies propose models for estimating particle concentration in cleanrooms, considering several operational characteristics. In this work, a new approach is proposed, airflow (air change per hour) is estimated and supplied to the controlled environment according to demand, generating energy savings by reducing fan speed. This technique uses a softsensor composed of a cleanroom particle concentration estimation model. Two softsensors technologies are used to achieve the proposed objective: the first one uses an estimation model with parameter correction through non-linear optimization with restrictions, while the second uses a Kalman filter estimator, even with measurement noise. As a case study, one of the cleanrooms of Unisinos itt-Chip Institute was used. The results revealed that under certain conditions and scenarios of room use, it is possible to reduce up to 75,6% of the energy consumed by the HVAC system fan. | en |
