Predicted Mean Vote with skin temperature from standard effective temperature model

Abstract

The accurate prediction of thermal comfort is crucial for optimally designing buildings with thermal comfort and energy efficiency. Predicted Mean Vote (PMV) is widely recognized by national and international standards for the prediction of thermal comfort. However, the low accuracy of the PMV has been criticized by various studies under different contextual scenarios. Given the importance of the skin temperature to thermal comfort and the simplification of the skin temperature by the PMV, this study modifies the PMV by replacing the simplified skin temperature with the skin temperature from the standard effective temperature model to improve the prediction quality of the PMV. The simplified skin temperature solely considers the effects of activity level, neglecting the effects of clothing insulation and environmental parameters. With a more complex human thermal regulation, the skin temperature obtained from the standard effective temperature model is more advanced. The modified PMV is validated by the ASHRAE Global Thermal Comfort Database II to mitigate the overestimation of warm and cold discomforts observed in the original PMV under different contextual scenarios (i.e., climate types, building types, and types of heating, ventilation and air conditioning). Overall, the modified PMV improves the accuracy and robustness of thermal sensation prediction by 62% and 56%, respectively. With the largely improved prediction quality, the modified PMV contributes to the update of thermal comfort standards and the development of energy-efficient and thermally comfortable buildings.