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An automobile seat’s thermal performance can be challenging to quantify since it requires comprehensive human subject testing. Seat manufacturers must rely on subjective ratings to understand how the construction of a seat and its underlying heating and cooling technology may compare to other seats. Other factors may influence seat ratings published by global marketing information services companies (e.g., JD Power and Associates). In particular, occupants may be biased by the vehicle class in which a seat is installed and by how much the contribution of a specific vehicle’s HVAC system performance affects the perception of seat thermal comfort. Therefore, there is a need for an objective testing methodology that does not rely on human participants but is still capable of producing a thermal performance rating in terms of established thermal comfort scales.

A test protocol previously developed for automotive applications was adapted to evaluate the performance of a climate control system for a heavy-duty truck. Human subjects, as well as a test system composed of a high-resolution passive sensor manikin and a human thermal model, were employed to evaluate thermal comfort perception. Testing was performed in a climate-controlled wind tunnel equipped with a dynamometer. The truck’s HVAC system performance was evaluated in a −10 °C environment. Additionally, the test protocol was designed to explore a large range of thermal sensation and comfort states. Subjective responses, including thermal sensation and comfort, as well as thermo-physiological state information, quantified by skin temperatures measured across the body, were obtained from the human test participants and compared to that which was indicated by the test system.

In a previous study, a passive sensor (HVAC) manikin coupled with a human thermal model was used to predict the thermal comfort of human test participants. The manikin was positioned among the test participants while they were collectively exposed to a mild transient heat up within a thermally asymmetric chamber. Ambient conditions were measured using the HVAC manikin’s distributed sensor system, which measures air velocity, air temperature, radiant heat flux, and relative humidity. These measurements were supplied as input to a human thermal model to predict thermophysiological response and subsequently thermal sensation and comfort. The model predictions were shown to accurately reproduce the group trends and the “time to comfort” at which a transition occurred from a state of thermal discomfort to comfort. In the current study, the effectiveness of using a coupled HVAC manikin-model system to evaluate a vehicle climate control system was investigated.

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.

Reliable assessment of occupant thermal comfort can be difficult to obtain within automotive environments, especially under transient and asymmetric heating and cooling scenarios. Evaluation of HVAC system performance in terms of comfort commonly requires human subject testing, which may involve multiple repetitions, as well as multiple test subjects. Instrumentation (typically comprised of an array of temperature sensors) is usually only sparsely applied across the human body, significantly reducing the spatial resolution of available test data. Further, since comfort is highly subjective in nature, a single test protocol can yield a wide variation in results which can only be overcome by increasing the number of test replications and subjects. In light of these difficulties, various types of manikins are finding use in automotive testing scenarios.

Accurate assessment of thermal comfort requires comprehensive analysis of the environmental effects contributing to the heat transfer to and from the human body. A common comfort evaluation approach (e.g. PMV/PPD, Equivalent Temperature) is to find a direct correlation of comfort to environmental conditions (e.g. air temperature, relative humidity, clothing), thus implicitly accounting for the relationship between physiological response and thermal comfort. An alternate approach (e.g. Berkeley Comfort Model, Fiala's DTS) is to explicitly correlate comfort to basic physiological response (e.g. skin and core temperature), thereby separating the thermal analysis portion of the problem from the more subjective comfort analysis portion. While it has been shown that comparable results can be obtained between environment-based comfort metrics and physiology-based comfort metrics, the latter should be employed for optimal prediction accuracy.

Virtual simulation of passenger compartment climatic conditions is becoming increasingly important as a complement to the wind tunnel and field testing to achieve improved thermal comfort while reducing the vehicle development time and cost. The vehicle cabin is subjected to various thermal environments. At the same time many of the design parameters are dependent on each other and the relationship among them is quite complex. Therefore, an experimental parametric study is very time consuming. The present 3-D RadTherm analysis coupled with the 3-D CFD flow field analysis takes into account the geometrical configuration of the passenger compartment which includes glazing surfaces and pertinent physical and thermal properties of the enclosure with particular emphasis on the glass properties. Virtual Thermal Comfort Engineering (VTCE) is a process that takes into account the cabin thermal environment coupled with a human physiology model.

An aircraft environmental control system (ECS) is commonly designed for a cabin that has been divided into several thermal control zones; each zone has an air flow network that pulls cabin air over an isolated thermocouple. This single point measurement is used by the ECS to control the air temperature and hence the thermal environment for each zone. The thermal environment of a confined space subjected to asymmetric thermal loads can be more fully characterized, and subsequently better controlled, by determining its “equivalent temperature.” This paper describes methodology for measuring and controlling cabin equivalent temperature. The merits of controlling a cabin thermal zone based on its equivalent temperature are demonstrated by comparing thermal comfort, as predicted by a “virtual thermal manikin,” for both air-temperature and equivalent-temperature control strategies.

This paper presents methodology for predicting body core temperature using the ASHRAE two-node thermoregulation model. Predicted changes in core temperature can be used to certify that, during a heat stress event, the temperature and humidity within an aircraft will not exceed values that are hazardous to the occupants. The use of ASHRAE model was validated by comparing its predictions to experimental data for subjects that were exposed to hot (33° to 48°C) environments. The model has been used to predict body core temperature in the cockpit and cabin during three different environmental ventilation system failure simulations for an aircraft that uses atmospheric air from the ram air duct in the event of a dual pack failure.