Adaptive‐rational thermal comfort model: Adaptive predicted mean vote with variable adaptive coefficient

Abstract

Thermal adaptations, as feedbacks of occupants to physical stimuli, extend thermal comfort zone thereby reducing building energy consumption effectively. The rational approach models thermal comfort from the perspective of the body's heat balance, but is limited in explaining the thermal adaptations. The adaptive approach of modeling thermal comfort can fully account for the thermal adaptations, but ignores the body's heat balance. To improve thermal comfort prediction, this study proposes an adaptive‐rational thermal comfort model, that is, an adaptive predicted mean vote with a variable adaptive coefficient (termed as arPMV). By linearly linking the negative feedback effects of the thermal adaptations to the ambient temperature according to the adaptive approach, the variable adaptive coefficient is linearly related to the reciprocal of the ambient temperature with two constants. The variable adaptive coefficient is determined by explicitly quantifying the two constants as the functions of the predicted mean vote, thermal sensation vote, and ambient temperature. The proposed arPMV is validated for naturally ventilated, air‐conditioned, and mixed‐mode buildings, with the mean absolute error and the robustness of the thermal sensation prediction reduced by 24.8%‐83.5% and improved by 49.7%‐83.4%, respectively.

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“…Secondly, the IJV system performs better than the MV system in IAQ and energy saving but worse in thermal comfort. The IAQ is suggested to have a higher priority than thermal comfort due to the high basic reproduction number of COVID-19, and the thermal comfort may be adaptive due to personal conditions [ 86 , 87 ], e.g., the difference in clothes. This content will be further optimized.…”

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