A new predictive thermal sensation index of human response

The purpose of this paper is to investigate the problem of determining a human thermal sensation index that can be used in feedback control of HVAC systems. We present a new approach based on fuzzy logic to estimate the thermal comfort level depending on the state of the following six variables: the air temperature, the mean radiant temperature, the relative humidity, the air velocity, the activity level of occupants and their clothing insulation. The new fuzzy thermal sensation index is calculated implicitly as the consequence of linguistic rules that describe humanʹs comfort level as the result of the interaction of the environmental variables with the occupantʹs personal parameters. The fuzzy comfort model is deduced on the basis of learning Fangerʹs ‘Predicted Mean Voteʹ (PMV) equation. Unlike Fangerʹs PMV, the new fuzzy PMV calculation does not require an iterative solution and can be easily adjusted depending on the specific thermal sensation of users. These characteristics make it an attractive index for feedback control of HVAC systems. The simulation results show that the new fuzzy PMV is as accurate as Fangerʹs PMV.