(Open access funding provided by University of Pécs)
Researchers have increasingly focused on thermal comfort, examining both individuals’
thermal sensations and the percentage of people dissatisfied with the thermal environment.
Most studies rely on the widely used PMV (Predicted Mean Vote) model and the PPD (Predicted
Percentage of Dissatisfied) value derived from it, both defined by the ISO 7730:2005
standard. However, previous studies have shown that this standardized method only
applies under steady-state conditions, which do not reflect the dynamic nature of
everyday environments. As closed-loop control technologies gain prominence in building
services, the need to evaluate thermal comfort under time-varying conditions has grown.
The standard method does not account for the thermal inertia of the human body, which
limits its applicability in such dynamic contexts. In this study, we develop a method
to estimate instantaneous thermal sensation under non-stationary conditions by incorporating
thermal inertia through signal processing techniques. This approach addresses a well-recognized
limitation of the standard PMV–PPD model and provides a way to assess thermal comfort
in real time. We collected experimental data using a thermal comfort measurement station,
a thermal manikin, and human subjects in a controlled climate chamber. The proposed
method enables real-time evaluation of thermal comfort in dynamic environments and
offers a foundation for integration into HVAC control and comfort optimization systems.
