Applicability of thermal comfort models to car cabin environments

Car cabins are non-uniform and asymmetric environments in relation to both air velocity and temperature. Estimating and controlling vehicle occupant thermal comfort is therefore a challenging task. This paper focuses on evaluating the suitability of four existing thermal comfort models, namely the Predicted Mean Vote (PMV), Taniguchi's model, Zhang's model and Nilsson's model in a variety of car cabin conditions. A series of comfort trials were performed ranging from controlled indoor trials to on-road driving trials. The outputs of all four models were compared to the sensation index reported by the subjects situated in the driver seat. The results show that PMV and Nilsson's model are generally applicable for the car cabin environment, but that they are most accurate when there is a small air temperature rate of change (of under 1.5 °C per minute), giving correlation levels of 0.91 and 0.93 for the two models respectively. Taniguchi's and Zhang's models were found unsuitable for all conditions, with correlation levels ranging between 0.03 and 0.60. Nilsson's model is recommended by the authors based on the level of agreement with the subjective reports, its ability to estimate both local and overall thermal sensation and the smaller number of input parameters.