Development and validation of online parameter estimation for HVAC systems

Improving the energy efficiency of buildings by examining their heating, ventilating, and air-conditioning (HVAC) systems represents an opportunity. To improve energy efficiency, to increase occupant comfort, and to provide better system operation and control algorithms for these systems, online estimation of system parameters, including system thermophysical parameters and thermal loads, is desirable. Several reported studies have presented simulation results and assumed that the thermal loads are known. A difficulty in HVAC system parameter estimation is that most HVAC systems are nonlinear, have multiple and time varying parameters, and require an estimate of the thermal loads for a building zone. In this study, building zones and variable-air-volume units are modeled. The system parameters including the thermal loads are estimated using the recursive-least-squares method with a variable forgetting factor. The sensitivity of the estimation results to different factors is examined. The estimated parameters are used to predict the zone and variable-air-volume-discharge-air temperatures. Several experiments are used to validate the prediction results. The comparisons show good agreement between the experiments and the prediction results.