Developing an experimental system identification method to extract air flow rates from room temperature measurements

Abstract

This thesis develops a system identification method which is capable of determining individual room air change rates by utilizing a combined low order physical modeling and experimental approach. Important aspects of this work include the development of the low order model, insight into the dominant thermal dynamics, development of the system identification method, and experiments which confirm the method. The low order model is shown to capture the dominant dynamics of the room air temperature response to a step change in the supply air flow rate with minimum levels of model complexity. Such a combined modeling and experimentally based system identification method is advantageous because it can be used to determine air flow rates for rooms throughout the building without utilizing numerically intensive CFD to model air flow or the more labor intensive methods of room-by-room air flow measurements. The energy used in operating a large buildings HVAC system scales with the air flow rate in the building, since a higher air volume results in higher energy expenditure for the fans to push the air and for the heating and cooling coils to condition the air. Older buildings, designed when energy costs were lower, typically utilize high air flow rates since this is the easiest way to meet ventilation and thermal requirements. However, HVAC energy usage can be reduced by minimizing these air flow rates while still meeting ventilation requirements. In order to achieve this, a tool capable of determining the air change rates on a room-by-room basis is required. This air change rate calculation method needs to be capable of performing the task without any pre-knowledge of the building and HVAC layout, since as buildings age their layouts can change, floor plans can be lost, and HVAC equipment can fall into disrepair. [TRUNCATED]