Study on Indoor Thermal Environment Control Based on Thermal Sensation Prediction

被引:7
|
作者
Han, Dianshan [1 ]
Li, Rui [2 ]
Wang, Fulin [1 ]
Sun, Zeyu [1 ]
Moon, Saejin [1 ]
Gong, Ziyang [3 ]
Yu, Wenhong [3 ]
Zhang, Yin [2 ]
机构
[1] Tsinghua Univ, Key Lab Indoor Air Qual Evaluat & Control, 1 Qinghuayuan, Beijing 100084, Peoples R China
[2] State Grid Shanghai Municipal Elect Power Co, 1758 Tianshan Rd, Shanghai 200122, Peoples R China
[3] North China Univ Technol, Sch Civil Engn, 5 Jinyuanzhuang Rd, Beijing 100144, Peoples R China
基金
中国国家自然科学基金;
关键词
Indoor thermal environment control; Thermal sensation prediction; Infrared imaging;
D O I
10.1016/j.proeng.2017.10.298
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Currently the indoor thermal environment control is mainly conducted based on the set points given by room occupants or based on PMV, which might cause problems of unreasonable temperature setting and unsatisfied individual thermal preferences of room occupants. The indoor thermal environment control method based on thermal sensation expression can solve these problems. However, control based on thermal sensation expression might frequently interrupt room occupants' concentrations on work because this method needs occupants to input their thermal sensations, when their comfortable temperature range changes with thedifferences of the metabolic rate, clothing level etc. In an attempt to solve this problems, a new indoor thermal environment control method is proposed, which is to collect occupants' skin temperature measured by infrared imaging to estimate the occupants' current thermal sensation and predict their future thermal sensations. This paper introduces the control method of the system based on thermal sensation prediction. The control method was verified by building the test-beds and conducting a series of experiments. Experiment results show that 98% of the evaluations are neutral/satisfied/very satisfied with this control system, which means the proposed indoor thermal environment control method based on thermal sensation prediction is feasible for actual application. (c) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:3072 / 3079
页数:8
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