Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

• Published in: Building and environment Vol. 153; pp. 205 - 217
• Main Authors: Cheung, Toby, Schiavon, Stefano, Parkinson, Thomas, Li, Peixian, Brager, Gail
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.04.2019; Elsevier BV
• Subjects: Accuracy; Air conditioners; Air temperature; ASHRAE Global Thermal Comfort Database II; Error detection; Mathematical models; Model accuracy; PMV–PPD model; Prediction; Prediction models; Thermal comfort; Ventilation; PMV–PPD model; Accuracy; Thermal comfort; ASHRAE Global Thermal Comfort Database II; Prediction
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2019.01.055

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. [Display omitted] •Assessed PMV-PPD accuracy using the ASHRAE Global Thermal Comfort Database II.•PMV predicted thermal sensation correctly only one out of three times.•PMV had a mean absolute error of one unit on the thermal sensation scale.•PPD was not able to predict the dissatisfaction rate.•PMV-PPD accuracy varied strongly between ventilation, building types and climate.