Abstract
In addition to ensuring the thermal comfort of occupants, monitoring and controlling indoor thermal environments can reduce the energy consumed by air conditioning systems. This study develops an additive model for predicting thermal comfort with rapid and simple arithmetic calculations. The advantage of the additive model is its comprehensibility to administrators of air conditioning systems, who are unfamiliar with the PMV–PPD model but want to adjust an indoor environment to save energy without generating complaints of discomfort from occupants. In order to generate the additive model, a laboratory chamber experiment based on matrix experiment using orthogonal array, was performed. By applying the analysis of variance on observed thermal sensation votes and percentage of dissatisfaction, the factor effects of environmental variables that account for the additive model were determined. Additionally, the applicability of the PMV–PPD model in hot and humid climates is discussed in this study, based on experimental results.
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