Nonlinear system identification of thermal dynamics in buildings

Standard (black-box) linear regression models may not necessarily suffice for accurate identification of thermal dynamics in buildings. This is particularly apparent when either a radiant-heating (RH) system or a heating-ventilation-air-conditioning (HVAC) system is used for temperature control and the flow rate of the thermal medium varies significantly. For this reason, this paper analytically derives, using physical insight, and investigates nonlinear regression models for system identification of thermal dynamics in buildings. The performance of these models is compared with standard (black-box) linear regression models through simulations.