Thermal Comfort Analysis for Passengers Inside a Vehicular Cabin
Published October 25, 2016 by SAE International in United States
Downloadable datasets for this paper availableAnnotation of this paper is available
The theory related to the thermal comfort of a human being is described in this article. It is not technically and economically feasible to provide optimal thermal comfort to a human being. The air temperature inside the vehicles is inhomogeneous mainly due to the ventilation system and to solar heat flux. The thermal stratification of air that results in difference of heat flux at the human body may cause thermal discomfort. In this case, it is important to quantify the degree of discomfort, which can be represented by the Predicted Mean Vote and Predicted Percentage Dissatisfied indices.
This study intends to determine the thermal comfort for a human being inside vehicular cabins considering just the ventilation system with the same ambient temperature. A cabin of a vehicle is virtually reproduced in FLUENT® and the methodology of thermal comfort, based on previous works from the literature, is developed in Matlab 2010a and applied in this simulation.
The results show the parameters of thermal comfort on the vehicle’s occupants. The results shows that the thermal comfort is not exclusively a function of air temperature, but also of others parameters, such as mean radiant temperature, relative air velocity, air humidity, activity level and clothing thermal resistance. The sun and the time of the day promote local discomfort and reduce the thermal acceptability of the space. In addition, the thermal stratification caused by the sunlight and the ventilation system also cause thermal discomfort. This work demonstrates the thermal comfort methodology and the application on vehicular cabins, which can be used to design more robust air conditioning system.
CitationMagazoni, F., Buscariolo, F., Maruyama, F., Sales, F. et al., "Thermal Comfort Analysis for Passengers Inside a Vehicular Cabin," SAE Technical Paper 2016-36-0197, 2016, https://doi.org/10.4271/2016-36-0197.
Data Sets - Support Documents
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