平均預測投票(英文:Predicted Mean Vote,PMV)模型是1970年代由堪薩斯州立大學和丹麥技術大學的Povl Ole Fanger教授所開發,而後被各國廣泛使用的热舒适模型。它是根据热平衡原理和在稳态条件下在受控气候室内收集的实验数据开发,適用於空調空間的熱舒適性評估[4]。研究人員發現,大多數人都會對一理想溫度感到满意。随着室溫逐漸偏離理想溫度,不满意現狀的比率會增加。可以藉由統計表示為通过舒适条件和预测的平均投票(PMV)表示满意的个人百分比。这种方法受到了ASHRAE 884项目开发的自适应舒适度模型的挑战。
1998年 De Dear 教授研究[2]發現 在中央空調的房間中,受測者的熱舒適感受乎與既有的PMV熱舒適模型完全相符。然而出乎他們意料的,平平都是室內空間,PMV模型對於自然通風房間的受測者熱舒適的解釋度就沒這麼高,受試者在自然通風房間對於溫度高低的容忍力似乎比較大(當室外氣溫若偏高,體感舒適溫度也會略微提升,反之亦同)。 因此提出了自適應模型(英文Adaptive Model),其構想是使試驗人員動態地与其周围环境互动。乘员通过衣服,可操作的窗户,风扇,个人取暖器和窗簾来控制其热环境 [5] 。PMV模型可以應用於空調空間,而自適應模型則能使用於自然通風空間[6]。
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^Predicted mean vote. www.designingbuildings.co.uk. [2021-01-07]. (原始内容存档于2021-01-27) (英国英语).
^ISO, 2005. ISO 7730 - Ergonomics of the thermal environment — Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria.
^CEN, 2019. EN 16798-1 - Energy performance of buildings - Ventilation for buildings. Part 1: Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics.
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