A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)

被引：509
作者：
Yao, Runming [1 ,3 ]
Li, Baizhan [2 ,3 ]
Liu, Jing [1 ]
机构：
[1] Univ Reading, Sch Construct Management & Engn, Reading RG6 6AW, Berks, England
[2] Chongqing Univ, Minist Educ, Key Lab Gorges Reservoir Regions Ecoenvironm 3, Chongqing, Peoples R China
[3] Chongqing Univ, Fac Urban Construct & Environm Engn, Chongqing, Peoples R China
来源：
BUILDING AND ENVIRONMENT | 2009年 / 44卷 / 10期
基金：
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词：
Thermal comfort; Thermal environment; Adaptive Predicted Mean Vote (aPMV); Predicted Mean Vote (PMV); Actual Mean Vote (AMV); Adaptive coefficient lambda; BUILDINGS; STANDARDS; PMV;
D O I：
10.1016/j.buildenv.2009.02.014
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
This paper presents in detail a theoretical adaptive model of thermal comfort based on the "Black Box" theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (lambda) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2089 / 2096
页数：8
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