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Modified predicted mean vote models for human thermal comfort: An ASHRAE database-based evaluation

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  • Li, Han
  • Hu, Haiyu
  • Wu, Zhiyao
  • Kong, Xiangfei
  • Fan, Man

Abstract

A comprehensive index that is straightforward to implement and reliable is essential for assessing and predicting human thermal comfort, integrating both energy efficiency and Indoor Environmental Quality (IEQ) considerations. The Predicted Mean Vote (PMV) and its associated correction models are extensively utilized to assess human thermal comfort, subsequently informing the design of indoor thermal environments. Hence, this study reviews the evolution of PMV models. Firstly, twenty PMV-modified models are summarized and categorized into four principal categories according to the correction methods. Secondly, the application of common modified models in engineering practice is listed and analyzed. Thirdly, a further evaluation of seven modified models has been conducted using ASHRAE Database I and II. The results demonstrate that PMVe and ePMV are suitable for evaluation in tropical and temperate regions and ePMV has the highest evaluation accuracy among all the discussed models. Finally, three extension directions of the PMV model are proposed to provide ideas for the subsequent revision. The outcomes of this study provide guidance for the appropriate selection and utilization of enhanced PMV models.

Suggested Citation

  • Li, Han & Hu, Haiyu & Wu, Zhiyao & Kong, Xiangfei & Fan, Man, 2025. "Modified predicted mean vote models for human thermal comfort: An ASHRAE database-based evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:rensus:v:209:y:2025:i:c:s1364032124007688
    DOI: 10.1016/j.rser.2024.115042
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    1. Huang, Yuting & Gong, Guangcai & Wang, Yuxin & Chen, Xiang & Shi, Xing & Liu, Jiaqing, 2025. "Investigation of energy consumption and local thermal comfort through the transient thermophysiological model and human-body exergy model for air-carrying energy system," Energy, Elsevier, vol. 328(C).

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