Abstract

Real-time thermal comfort evaluation is not only essential in constructing the control module of Heating, Ventilation and Air Conditioning (HVAC) systems in residential buildings but also rather critical in energy conservation. In the transient thermal environment, current thermal comfort is not stable and varies from time to time. Therefore, if we only evaluate the current thermal sensation that will cause prediction error. Existing thermal comfort models mainly focus on the evaluation of current thermal comfort. However, research on the evaluation of thermal sensation variation trend is vacant. Furthermore, since individual differences play an important role in thermal comfort evaluation, physiological indices should be considered. To solve this problem, in this paper, the authors exclusively propose the concept of relative thermal sensation which accounts for the thermal sensation variation trend and give its real-time evaluation method by analysis of skin/clothes temperatures of ten local body segments using machine learning algorithms. By incorporating the relative thermal sensation model with an ordinary thermal comfort model, a novel complex thermal comfort model is derived, which has the ability to predict the current thermal comfort and the thermal sensation variation trend simultaneously and provides an early warning mechanism for thermal discomfort.

Highlights

  • Thermal comfort evaluation is essential in optimizing thermal comfort and constructing the control module of Heating, Ventilation and Air Conditioning (HVAC) systems in residential buildings and rather critical in energy conservation [2]–[4]

  • The clothes surface temperatures have a relatively higher variance than that measured on the skin surface since the clothes have a heat insulation effect

  • The forehead reached the highest temperature than other body segments; the shin and foot temperatures had a higher variance than that of the abdomen, the chest, and the back since the latter three local body segments occupy the trunk of the body while the former two local body segments are the body branches

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Summary

Introduction

A. THERMAL COMFORT EVALUATION BY PHYSIOLOGICAL INDICES. Thermal comfort evaluation has become a hot topic in recent years. The ASHRAE Standard 55-2017 [1], published by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), defined thermal comfort as ‘‘the condition of mind that expresses satisfaction with the thermal environment and is assessed by subjective evaluation’’ [1]. Thermal comfort evaluation is essential in optimizing thermal comfort and constructing the control module of Heating, Ventilation and Air Conditioning (HVAC) systems in residential buildings and rather critical in energy conservation [2]–[4]. Empirical formulas based models such as the Precited Mean Vote/Predicted Percentage of Dissatisfied (PMV/PPD) method [5]–[9] have the ability to predict the averaged thermal comfort over a large majority of people. The PMV/PPD method lacks the ability to account for individual differences.

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