基于动态热舒适的空调控制方案研究
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摘要
热舒适指标应用于空调的控制是空调控制的发展潮流,本文对动态热舒适指标控制进行了的一定的研究。由于目前并无合适的动态热舒适指标和模型,研究仍旧采用PMV指标。这里动态热舒适控制是指PMV在一个相对较大的范围有规律的变化,PMV值并不总是在舒适范围内,但动态过程的等效PMV值应该是合乎舒适要求的。根据研究,稳态热舒适易造成人体热适应能力的降低,空调基于动态热舒适的控制在节能和健康性上都有不错的效果。
编制了PMV的计算程序,并和商业软件进行了对比,确保程序的准确性。本文还对用BP神经网络智能预测PMV进行了研究,最终输出误差达到使用要求。
本文计算分析了空调环境里热舒适六种因素对PMV的影响,根据动态热环境下人体热感觉TSV的实验数据,并通过计算对热舒适的六个影响因素不同组合下动态热环境TSV的值进行了修正。和稳态热舒适控制以及传统温度控制进行了比较,证明了28～31℃、风速为0.3m/s～1.2m/s的动态空调方案对于新陈代谢率1.2met以下的一般热环境,都可使等效PMV不超过1.0,且标准条件下室内设定温度可以有较大的提高。在此基础上对家用空调加个人风扇的方案进行了探讨,并分析了此模式下,家用空调的动态温度和风速的控制方案。该风扇直接对人提供模拟自然风的等温风,尤其是在控制系统不开压缩机的情况下,由该风扇的独立送风保障热舒适。经过计算分析,明确了该方案和稳态热舒适控制方案相比的节能效果。
本文通过对动态热舒适的初步的研究,结合我国空调企业研发、生产现状,得出一套家用空调结合个人风扇的温度和风速的动态控制方案。
Control based on dynamic thermal comfort index had been studied as there is a developing tide to apply thermal comfort index for air-conditioning control. Up to now there is not appropriate dynamic thermal comfort index and model, PMV index is still used in the study. Here dynamic thermal comfort control means that PMV should not be always in comfort zone but regularly changed within a relatively big range while its equivalent PMV still conform with comfort demand. From some research we know that air-conditioning control based on dynamic thermal comfort index has good effect on both energy saving and health while steady thermal comfort is prone to decrease human body' s thermal adaptability.The results gained from the PMV computer program edited in this paper are compared with comercial soft and the precision is proved to be ok. Besides, uses BP artificial neural net work(ANN) to predicted PMV index intelligently and the output error reaches the application accuracy demand.Calculates and analyses the impact of the six factors of thermal comfort to the PMV index in the air-conditioning environment. TSV under dynamic thermal environment with a variety of combination of six influencing factors to thermal comfort is revised through computing and experiment data of human body' s TSV. Compared with steady thermal comfort control and conventional set-point temperature control it' s proved that equivalent PMV should not exceed 1. 0 in usual thermal environment with metabolism under 1. 2 met for dynamic air-conditioning scheme;moreover, indoor set temperature can be heightened greatly under standard conditions. On the basis of the above research the concept of using room air conditioner and a personal fan at the same time is discussed in the thesis and the control scheme of the temperature and air velocity in this mode is analyzed. The additional personal fan directly provides the constant temperature airflow of the simulating natural winds for people;
it will assure the thermal comfort independently especially when control system turn off the compressor.In this paper, a set of control scheme of dynamic temperature and air velocity for room air conditioner with a additional personal fan through the elementary study of dynamic thermal comfort combined with the research and manufacture status of air-conditioning factory in our country. By computing and analyzing we get the energy savings effect of the scheme compared with static thermal comfort control.
编制了PMV的计算程序,并和商业软件进行了对比,确保程序的准确性。本文还对用BP神经网络智能预测PMV进行了研究,最终输出误差达到使用要求。
本文计算分析了空调环境里热舒适六种因素对PMV的影响,根据动态热环境下人体热感觉TSV的实验数据,并通过计算对热舒适的六个影响因素不同组合下动态热环境TSV的值进行了修正。和稳态热舒适控制以及传统温度控制进行了比较,证明了28～31℃、风速为0.3m/s～1.2m/s的动态空调方案对于新陈代谢率1.2met以下的一般热环境,都可使等效PMV不超过1.0,且标准条件下室内设定温度可以有较大的提高。在此基础上对家用空调加个人风扇的方案进行了探讨,并分析了此模式下,家用空调的动态温度和风速的控制方案。该风扇直接对人提供模拟自然风的等温风,尤其是在控制系统不开压缩机的情况下,由该风扇的独立送风保障热舒适。经过计算分析,明确了该方案和稳态热舒适控制方案相比的节能效果。
本文通过对动态热舒适的初步的研究,结合我国空调企业研发、生产现状,得出一套家用空调结合个人风扇的温度和风速的动态控制方案。
Control based on dynamic thermal comfort index had been studied as there is a developing tide to apply thermal comfort index for air-conditioning control. Up to now there is not appropriate dynamic thermal comfort index and model, PMV index is still used in the study. Here dynamic thermal comfort control means that PMV should not be always in comfort zone but regularly changed within a relatively big range while its equivalent PMV still conform with comfort demand. From some research we know that air-conditioning control based on dynamic thermal comfort index has good effect on both energy saving and health while steady thermal comfort is prone to decrease human body' s thermal adaptability.The results gained from the PMV computer program edited in this paper are compared with comercial soft and the precision is proved to be ok. Besides, uses BP artificial neural net work(ANN) to predicted PMV index intelligently and the output error reaches the application accuracy demand.Calculates and analyses the impact of the six factors of thermal comfort to the PMV index in the air-conditioning environment. TSV under dynamic thermal environment with a variety of combination of six influencing factors to thermal comfort is revised through computing and experiment data of human body' s TSV. Compared with steady thermal comfort control and conventional set-point temperature control it' s proved that equivalent PMV should not exceed 1. 0 in usual thermal environment with metabolism under 1. 2 met for dynamic air-conditioning scheme;moreover, indoor set temperature can be heightened greatly under standard conditions. On the basis of the above research the concept of using room air conditioner and a personal fan at the same time is discussed in the thesis and the control scheme of the temperature and air velocity in this mode is analyzed. The additional personal fan directly provides the constant temperature airflow of the simulating natural winds for people;
it will assure the thermal comfort independently especially when control system turn off the compressor.In this paper, a set of control scheme of dynamic temperature and air velocity for room air conditioner with a additional personal fan through the elementary study of dynamic thermal comfort combined with the research and manufacture status of air-conditioning factory in our country. By computing and analyzing we get the energy savings effect of the scheme compared with static thermal comfort control.
引文
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[2] 贾衡 主编.人与建筑环境.北京工业大学出版社,2001.
[3] 魏庆芃,谭刚,王鹏.建筑生态环境与节能效果综合评价.清华同方技术通讯,2000,10.
[4] Alan E. Luedtke, etc.. INDOOR ENVIRONMENTAL MANAGEMENT. World Workplace' 99, IFMA, October 3-5, 1999, Los Angeles, California.
[5] 金招芬,朱颖心 主编.建筑环境学.中国建筑工业出版社,2001.
[6] 周兴禧.变频空调系统特性的仿真研究.流体机械,2000,Vol.28(2):43-47.
[7] Wai L. Tse, Albert T.P. So, and C. Eng..Implementation of Comfort-Based Air-Handing Unit Control Algorithms. ASHRAE Trans. 2000,106(1):29-44.
[8] K.H. Yang, C.H. Su. An approach to building energy savings using the PMV index. Building and Environment, 1997, Vol. 32, No.1, pp. 25-30.
[9] MacArthur, J.W. 1986. Humidity and predicted-mean-vote based(PMV based) comfort control. ASHRAE mransactions. 92(1B):5-17.
[10] Simmonds P. Thermal comfort and optimal energy use. ASHRAE Transactions, 99(1):1037-1048.
[11] Henderson, H. I., K. Rengarajan, and D. B. Shirley. 1992. The impact of comfort control on air conditioner energy usein humid climates. ASHRAE Transactions, 1992, 98(2):104-113.
[12] 赵荣义.关于“热舒适”的讨论.暖通空调,2000,(3):35-37.
[13] 赵荣义,许为全.改善室内空气环境的调节策略.暖通空调,1997,27(1):1-4.
[14] KEFTON, ROBERT W. Physiological Adjustments of Human Beings to Sudden Change in Environment[J]. ASHPAE Transactions, 1947, (53): 327-356.
[15] 龙惟定,白玮.我国民用建筑空调的发展前景.2000年全国空调与热泵节能技术交流会.
[16] 清华大学建筑学院生态住宅研究小组.生态住宅.www.hvacr.com.cn/…
[17] 涂逢祥.建筑节能·37.中国建筑工业出版社,2002.
[18] 龙惟定,潘毅群,白玮.智能建筑的室内生态环境.暖通空调,2001,31(4):75-78.
[19] 封跃鹏,张太生.室内空气污染概述.环境监测管理与技术,2002(3):17-20.
[20] Kaya A., C.S. Chen, S. Raina and S.J. Alexander. Optimum control policies to minimize energy use in HVAC systems. ASHRAE Transactions, 88(2):235-248.
[21] D.G. Scheatzle, Arch. D.,P.E.,AIA. The Development of PMV-Based Control for a Residence in a Hot Arid Climate. ASHRAE Transactions. 1991.97(2):1002-1019.
[22] Sunao Funakoshi, Kazuya Matsuo. PMV-BASED TRAIN AIR-CONDITIONING CONTROL SYSTEM[J]. ASHRAE Trans. 1995, Part Ⅰ:423-430.
[23] 张良杰等.基于神经网络与模糊逻辑控制技术的“舒逸”智能空调控制器.制冷学报,1994,3:54-57.
[24] 叶国栋.舒适空调中的热舒适指标控制研究.湖南大学硕士学位论文,2002.
[25] 金英姿.动态热环境中人体热健康的探讨.黑龙江大学自然科学学报,2003,20(3): 89-92.
[26] 郭富军,杨昌智.热舒适指标在空调系统控制中的应用研究.湖南大学学报,2000 (9).
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