Comparative analysis of modified PMV models and SET models to predict human thermal sensation in naturally ventilated buildings

Jie Gao, Yi Wang, Pawel Wargocki

Research output: Contribution to journalJournal articleResearchpeer-review


In this paper, a comparative analysis was performed on the human thermal sensation estimated by modified predicted mean vote (PMV) models and modified standard effective temperature (SET) models in naturally ventilated buildings; the data were collected in field study. These prediction models were developed on the basis of the original PMV/SET models and consider the influence of occupants' expectations and human adaptive functions, including the extended PMV/SET models and the adaptive PMV/SET models. The results showed that when the indoor air velocity ranged from 0 to 0.2m/s and from 0.2 to 0.8m/s, the expectancy factors for the extended PMV model and the extended SET model were from 0.770 to 0.974 and from 1.330 to 1.363, and the adaptive coefficients for the adaptive PMV model and the adaptive SET model were from 0.029 to 0.167 and from-0.213 to-0.195. In addition, the difference in thermal sensation between the measured and predicted values using the modified PMV models exceeded 25%, while the difference between the measured thermal sensation and the predicted thermal sensation using modified SET models was approximately less than 25%. It is concluded that the modified SET models can predict human thermal sensation more rationally and accurately compared with the modified PMV models in naturally ventilated buildings probably because air velocity has a strong effect on human thermal sensation in naturally ventilated buildings.
Original languageEnglish
JournalBuilding and Environment
Pages (from-to)200-208
Number of pages9
Publication statusPublished - 2015


  • Human thermal sensation
  • Modified PMV models
  • Modified SET models
  • Naturally ventilated building


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