Abstract
Since the thermal environment in a vehicle compartment is not uniform, the thermal sensation differs locally. Then for the improvement of air-conditioning property in the vehicle compartment, the evaluation method of local comfort is required, which has not been established yet. The purpose of this research is to develop the "dispersed two-node model" to predict regional skin temperature. The new model is derived based on the two-node model and intended to have following features; 1) Calculates heat balance at each part with two-node model. 2) Core temperature, which is assumed to correspond to arterial blood temperature, is common to each part. 3) The effect of heat entrainment by the circulation of blood is taken into consideration. 4) Skin temperature is distributed locally. 5) The property of the temperature regulation is based on the detailed model. 6) An adequate heat conductance for the regional compartment is identified to predict skin temperature in a practical precision. To reflect above features, the heat balance equation at regional compartment of the body is derived. S_i=M-Q_<res>-W_<ex>-(Q_<ci>+Q_<wi>-Q_<si>+Q_<ei>) This equation is solved by the time marching algorithm with parameters of transient local skin temperature and core temperature. Dry heat loss from the human body to the environment is calculated at the surface of the clothing. In this paper, Q_<ci>, Q_<ri> and Q_<si> are supposed to be given experimentally or theoretically as an input condition. Remainders are calculated by the similar way as that of the two-node model. Using the above equation, transient heat storage rate of S_i is calculated. Steady state is obtained when the sum of S_i becomes zero. In this model, total thermoregulatory values are divided into regional values by distribution factors which are determined by arranging properties of detailed model. To achieve the target precision, the experiments with a few subjects on the typical summer condition in the vehicle where an air-conditioner is working are performed so that adequate heat conductance values are identified. Finally, by applying this method to the prediction of the environment where radiative heat load is uneven, it is proved this method gives practical precision.
