PMV model and the adaptive model
The PMV model is based on extensive American and European experiments involving over a thousand subjects exposed to well-controlled environments. The studies showed that the thermal sensation is closely related to the thermal load on the effector mechanisms of the human thermoregulatory system. The PMV model predicts the thermal sensation as a function of activity, clothing and the four classical thermal environmental parameters. The advantage of this is that it is a flexible tool that includes all the major variables influencing thermal sensation. It quantifies the absolute and relative impact of these six factors and can therefore be used in indoor environments with widely differing HVAC systems as well as for different activities and different clothing habits. The PMV model has been validated in climate chamber studies in Asia as well as in the field, most recently in ASHRAE’s worldwide research in buildings with HVAC systems that were situated in cold, temperate and warm climates and were studied during both summer and winter. The PMV is developed for steady-state conditions but it has been shown to apply with good approximation at the relatively slow fluctuations of the environmental parameters typically occurring indoors. Immediately after an upward step-wise change of temperature, the PMV model predicts well the thermal sensation, while it takes around 20 min at temperature down-steps .
Field studies in warm climates in buildings without air-conditioning have shown, however, that the PMV model predicts a warmer thermal sensation than the occupants actually feel. For such non-air-conditioned buildings an adaptive model has been proposed. This model is a regression equation that relates the neutral temperature indoors to the monthly average temperature outdoors. The only variable is thus the average outdoor temperature, which at its highest may have an indirect impact on the human heat balance. An obvious weakness of the adaptive model is that it does not include human clothing or activity or the four classical thermal parameters that have a well-known impact on the human heat balance and therefore on the thermal sensation. Although the adaptive model predicts the thermal sensation quite well for non-air-conditioned buildings of the 1900’s located in warm parts of the world, the question remains as to how well it would suit buildings of new types in the future where the occupants have a different clothing behavior and a different activity pattern.
Why then does the PMV model seem to overestimate the sensation of warmth in non-air-conditioned buildings in warm climates? There is general agreement that physiological acclimatization does not play a role. One suggested explanation is that operable windows in naturally ventilated buildings should provide a higher level of personal control than in air-conditioned buildings. We do not believe that this is true in warm climates. Although an operable window sometimes may provide some control of air temperature and air movement, this applies only to the persons who work close to a window. What happens to persons in the office who work far away from the window? We believe that in warm climates air-conditioning with proper thermostatic control in each space provides a better-perceived control than openable windows.
Another factor suggested as an explanation to the difference is the expectations of the occupants. We think this is the right factor to explain why the PMV overestimates the thermal sensation of occupants in non-air-conditioned buildings in warm climates. These occupants are typically people who have been living in warm environments indoors and outdoors, maybe even through generations. They may believe that it is their “destiny” to live in environments where they feel warmer than neutral. This may be expressed by an expectancy factor, e. The factor e may vary between 1 and 0.5. It is 1 for air-conditioned buildings.
For non-air-conditioned buildings, the expectancy factor is assumed to depend on the duration of the warm weather over the year and whether such buildings can be compared with many others in the region that are air-conditioned. If the weather is warm all year or most of the year and there are no or few other air-conditioned buildings, e may be 0.5, while it may be 0.7 if there are many other buildings with air-conditioning. For non-air-conditioned buildings in regions where the weather is warm only during the summer and no or few buildings have air-conditioning, the expectancy factor may be 0.7 to 0.8, while it may be 0.8 to 0.9 where there are many air-conditioned buildings. In regions with only brief periods of warm weather during the summer, the expectancy factor may be 0.9 to 1. Table 1 proposes a first rough estimation of ranges for the expectancy factor corresponding to high, moderate and low degrees of expectation.
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