Analysis of the accuracy on PMV - PPD model using the ASHRAE Global Thermal Comfort Database II
Analysis of the accuracy on PMV - PPD model using the ASHRAE Global Thermal Comfort Database II
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DOI：
10.1016/j.buildenv.2019.01.055
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发表时间：
2019-04-15
影响因子：
7.4
通讯作者：
Brager, Gail
中科院分区：
文献类型：
--
作者：
Cheung, Toby;Schiavon, Stefano;Brager, Gail
预测平均投票率（PMV）和预测不满意率（PPD）是目前应用最广泛的热舒适性指标。然而，他们的表现仍然是一个有争议的话题。ASHRAE全球热舒适数据库II是同类中最大的，用于评估PMV/PPD模型的预测精度。我们的重点是：（i）PMV在预测观察到的热感觉（OTS）或观察到的平均投票（OMV）方面的准确性，以及（ii）将PMV-PPD关系与分组的OTS -观察到的不可接受百分比（OPU）进行比较。PMV预测OTS的准确性仅为34%，这意味着三分之二的热感觉预测错误。PMV在热感觉量表上的平均绝对误差为一个单位，其准确性在热感觉量表的两端下降。对于空调、自然通风和混合模式的建筑物，PMV的准确性同样较低。此外，PPD无法预测不满意率。如果PMV模型可以完美地预测热感觉，那么PPD准确性在接近中性时更高，但在中性之外，它会高估约15-25%的不满。此外，PMV-PPD准确性在通风策略、建筑类型和气候组之间变化很大。这些发现表明PMV-PPD模型的预测精度较低，表明需要开发高预测精度的热舒适模型。为了证明，我们开发了一个简单的热预测模型，只是基于空气温度和它的准确性，对于这个数据库，高于PMV。
The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) are the most widely used thermal comfort indices. Yet, their performance remains a contested topic. The ASHRAE Global Thermal Comfort Database II, the largest of its kind, was used to evaluate the prediction accuracy of the PMV/PPD model. We focused on: (i) the accuracy of PMV in predicting both observed thermal sensation (OTS) or observed mean vote (OMV) and (ii) comparing the PMV-PPD relationship with binned OTS - observed percentage of unacceptability (OPU). The accuracy of PMV in predicting OTS was only 34%, meaning that the thermal sensation is incorrectly predicted two out of three times. PMV had a mean absolute error of one unit on the thermal sensation scale and its accuracy decreased towards the ends of the thermal sensation scale. The accuracy of PMV was similarly low for air-conditioned, naturally ventilated and mixed-mode buildings. In addition, the PPD was not able to predict the dissatisfaction rate. If the PMV model would perfectly predict thermal sensation, then PPD accuracy is higher close to neutrality but it would overestimate dissatisfaction by approximately 15-25% outside of it. Furthermore, PMV-PPD accuracy varied strongly between ventilation strategies, building types and climate groups. These findings demonstrate the low prediction accuracy of the PMV-PPD model, indicating the need to develop high prediction accuracy thermal comfort models. For demonstration, we developed a simple thermal prediction model just based on air temperature and its accuracy, for this database, was higher than PMV.