Assessment of PMV accuracy for different geographic locations using the ASHRAE Thermal Comfort Database II

Abstract

Energy use minimization and cost reduction are common goals when talking about indoor climates. However, it is also necessary to assure indoor air quality and thermal comfort. The Predicted Mean Vote (PMV), as presented in the International Standard ISO 7730, is the most widely used thermal comfort index for assessing indoor thermal environments. This index takes into account indoor environmental parameters, including air temperature, radiant heat, relative humidity, air velocity, and personal parameters such as metabolism rate as well as clothing. Despite its wide application, this index was developed for a particular group of people in a specific region, not taking into account personal preferences, and, for these reasons, the accuracy of this model has been questioned. A solution proposed to overcome this discrepancy consists in applying a regional factor that generalizes the PMV to a specific region. Consequently, several studies have been carried out to verify the deviations between the index prediction and the actual thermal comfort. ASHRAE took the initiative to create a database with several studies that included thermal comfort and predictive indices. Thus, the study aims to access the database and to find patterns between the Predicted Mean Vote and the Actual Mean Vote, evaluate the accuracy of the index for different regions, comparing countries with different climatic conditions and characteristics to check for inconsistencies. In this way, it is intended to map European Countries in clutches according to their climatic zone and evaluate the PMV differences. This approach allows performing a correlation for specific climatic zones and obtaining an adjustment factor to apply in future calculations of the PMV index. The results show that the accuracy of the thermal comfort models decreases for regions further from comfort, pointing the need for adjustment of the model.