Abstract

Thermal comfort field experiments were conducted to acquire thermal comfort data of 119 participants in a test house representative of a typical UK house. This paper compares the performance of popular PMV-based thermal comfort index vs neutral temperature based on Actual Mean Vote. The aim of this research was to incorporate vertical thermal gradient, which is usually a neglected yet highly influential parameter in a residential setting and propose a new adaptive thermal comfort model. The new adaptive model (LPMV) has been developed using a polynomial curve fit method. This method was chosen as it has the capability to correlate indoor environmental parameters with AMV and incorporated them in the generated mathematical model. The model requires temperature gradient and SET* only to determine neutral temperatures which makes it the first of its kind. The LMPV model was rigorously tested against thermal comfort data compiled in this study and against independent/unbiased data (the ASHRAE RP-884 database). LPMV showed up to 0.7°C improvement in predicting neutral temperature of occupants compared to the famous Fanger’s PMV model. This can result in better prediction of a suitable heating setpoint temperature which has great implications on annual energy demand.

Keywords: Thermal comfort; Building physic; Temperature gradient; Fanger; AMV; PMV