Hepokoski, M., Curran, A., Gullman, S., and Jacobsson, D., "Coupling a Passive Sensor Manikin with a Human Thermal Comfort Model to Predict Human Perception in Transient and Asymmetric Environments," SAE Int. J. Passeng. Cars - Mech. Syst. 10(1):135-140, 2017, doi:10.4271/2017-01-0178.
Passive sensor (HVAC) manikins have been developed to obtain high-resolution measurements of environmental conditions across a representative human body form. These manikins incorporate numerous sensors that measure air velocity, air temperature, radiant heat flux, and relative humidity. The effect of a vehicle’s climate control system on occupant comfort can be characterized from the data collected by an HVAC manikin. Equivalent homogeneous temperature (EHT) is often used as a first step in a cabin comfort analysis, particularly since it reduces a large data set to a single intuitive number. However, the applicability of the EHT for thermal comfort assessment is limited since it does not account for human homeostasis, i.e., that the human body actively counter-balances heat flow with the environment to maintain a constant core temperature. For this reason, a thermo-physiological human model is required to accurately simulate the body’s dynamic response to a changing environment. Consequently, thermo-physiological based comfort models are preferred for analyzing transient and asymmetric environments since they relate sensation and comfort to body temperatures rather than to environmental conditions.This paper demonstrates that coupling a thermal comfort model with a passive sensor manikin can accurately predict the overall comfort reported by a group of individuals. A test protocol was developed to expose a group of human subjects to mildly asymmetric radiant conditions and a slow change in ambient temperature. An HVAC manikin was positioned among the test participants. The HVAC manikin measurements were input to a human model so that thermal sensation and comfort could be predicted and compared to the values recorded by the human subjects. Model predictions were shown to accurately reproduce the group trends and the “time to comfort” at which a transition occurred from a state of discomfort to comfort.