Elsevier

Building and Environment

Volume 44, Issue 10, October 2009, Pages 2089-2096
Building and Environment

A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)

https://doi.org/10.1016/j.buildenv.2009.02.014Get rights and content

Abstract

This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.

Introduction

Thermal comfort is defined by ASHRAE Standard 55-92 [1] as the condition of mind that expresses satisfaction with the thermal environment. Two kinds of approach exist in contemporary thermal comfort research: they are heat balance models based on laboratory studies and adaptive models based on field studies. The classic work of Fanger related thermal sensation to the existence of heat balance by observing a large number of people in laboratory experiments [2]. Fanger has established a lab-based PMV–PPD method. The work of Humphreys, based on his survey of field studies [3], has concluded that preferred temperatures are variable, responding to the monthly mean ambient temperature. Both methods have been supported by a large number of laboratory and field studies.

Thermal comfort standards determine the energy consumption by a building's environmental systems, therefore they play an important role in building sustainability. International standards such as ISO 7730 [4] and the ASHRAE Standard 55-92 [1] define comfort zones by applying Fanger's lab-based PMV–PPD method. It is suggested that a relationship based on laboratory experiments should be tested in the field before being included in a standard [5]. The thermal comfort standard has been challenged by the claim that energy saving will be achieved by switching from the traditional PMV–PPD based comfort standard to an adaptive comfort standard [6]. Thereafter, an Adaptive Comfort Standard ANSI/ASHRAE 55-2004 has been updated to the ASHRAE Standard 55 [7].

The aim of this paper is to present the results of the relationship between the Adaptive Predicted Mean Vote (aPMV) from the field study and the Predicted Mean Vote (PMV) from Fanger's Laboratory study. A theoretical adaptive model of thermal comfort, aPMV model, has been developed.

The Predicted Mean Vote (PMV) and Percentage People Dissatisfied (PPD) method [2] developed by Fanger has been used worldwide to predict and assess indoor thermal comfort in buildings. As a result, the PMV model has been an international standard since the 1980s [4]. The PMV model is based on extensive American and European experiments involving over a thousand subjects exposed to well-controlled, extensive and rigorous laboratory environments. This approach seeks to capture people's responses to the thermal environment in terms of the physics and physiology of heat transfer. The heat balance model indicates that the thermal sensation is closely related to the thermal load on the effect mechanisms of the human thermoregulatory system [2]. The most important variables, which influence a human's thermal comfort, are activity levels, the thermal resistance of clothing, air temperature, relative air velocity and the water vapour pressure in ambient air [2]. The method takes into account the combined impact of these variables on thermal comfort. The thermal comfort equation based on body heat balance in steady state condition ‘Predicted Mean Vote’ (PMV) predicts the mean thermal sensation vote on a standard scale for a large group of persons for any given combination of the four thermal environment variables, the activity level and the clothing value worn by the occupants.

The adaptive comfort theory was first proposed in the 1970s in response to the huge increases in oil price [8]. The adaptive approach to thermal comfort is based on the findings of surveys of thermal comfort conducted in the field. The fundamental assumption of the adaptive approach is expressed by the adaptive principle: if change occurs such as to produce discomfort, people react in ways which tend to restore their comfort [9]. In field studies, people flexibly adapted their behaviour to ensure thermal comfort through various approaches. The adaptive hypothesis states that one's satisfaction with an indoor climate is achieved by matching the actual thermal environmental conditions prevailing at that point in time and space with one's thermal expectations of what the indoor climate should be like [8].

In a field study, researchers usually collect data on the thermal environment and the simultaneous thermal response of subjects. Humphreys is the pioneer who found a statistically significant relationship between the indoor neutral temperature and the indoor air temperature prevailing at the same time and space [8]. It is well known that the prevailing indoor air temperature, to a great extent, is influenced by the outdoor climate. The statistical relationship can be found in Humphreys [3] and Auliciems [10]. Field studies in naturally ventilated buildings have shown that the PMV predicts thermal sensations warmer than those that the occupants actually feel in the naturally ventilated buildings [8].

The adaptive model reveals that the thermal comfort temperature is a function relating to the outdoor air temperature. Auliciems was the first to propose the adaptive control algorithm (ACA) in 1986 [10]. Humphreys, Nicol, Auliciems, de Dear, CIBSE and other researchers have also presented several empirical equations for the indoor thermal comfort temperature based on the different surveys of free-running buildings [11], [12], [13], [14], [15], [16].

The universal applicability of the PMV model has been debated for a long time. It is argued that the rigorous restrictions of environmental parameters such as air temperature, velocity and relative humidity in laboratory experiments are quite different from those in real buildings [6], [17], [18], [19], [20], [21], [22], [23]. It is argued that a relationship based on laboratory experiments should be tested in the field before inclusion in a standard [5]. Fanger [24] claimed that ‘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’. He argued that, although the adaptive model predicts the thermal sensation quite well for non-air-conditioned buildings in the late 20th century 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 may wear different clothing and change their activity pattern.

Field study surveys on thermal comfort have brought the PMV model into question. According to the steady-state heat-balance theory, the human body is a passive recipient of outdoor thermal stimuli, rather than an active one interacting with the person–environment system via multiple feedback loops [8]. It does not take into account adaptations of the human body, which play a key role in determining subjective thermal sensation and perception. It has been claimed that the ISO 7730, which is based on the heat balance model, overestimates the occupant responses on the ASHRAE scale at high temperatures and underestimates them at low temperatures [25]. This will lead to the use of more air conditioning than is necessary.

There is a great need to carry out an in-depth study on the adaptive model both theoretically and practically. It is to be hoped that the adaptive model can be based on a theory which has been successfully tested against wide-ranging empirical results. de Dear claimed that the adaptive and heat balance approaches to modelling thermal comfort are complementary rather than contradictory [8]. At some level, the static heat balance model can be considered as being partially adaptive in the behavioural sense since it accounts for clothing, activity level and indoor climatic parameters which can be adjusted by the occupants [8].

It is believed that only a combination of the features of both these modelling approaches will eventually be able to account for both the thermal and non-thermal influences on occupant response in real buildings [6].

Section snippets

Fanger's extension of PMV

In accordance with the debate on the discrepancies between the PMV model and the Actual Mean Vote (AMV) in a warm climate, Fanger and Toftum [24] proposed an extended PMV model which incorporated an ‘expectancy factor, e’, the main factor explaining why PMV overestimates the thermal sensation of occupants in non-air-conditioned buildings in a warm climate, in order to widen the applicability of the thermal index of PMV derived from laboratory research based on conventional heat-balance theory.

Survey and experimental study

In order to find out the value of the adaptive coefficient λ in the Adaptive Predicted Mean Vote model, a field study has been carried out in free-running buildings in Chongqing, a typical hot summer and cold winter city in China [35], by using a subjective questionnaire survey simultaneous with thermal environmental parameter monitoring. The purpose of the subjective questionnaire survey is to find out the discrepancies between the subjects' Actual Mean Vote (AMV) and the PMV calculated based

Data analysis and results

Fig. 4, Fig. 5 show that for the same level of indoor air temperature, the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in summer and is less than the AMV in winter. This phenomenon reflects the fact that occupants by behavioural adaptation can achieve thermal comfort at a relatively higher indoor air temperature in summer and a relatively lower indoor air temperature in winter compared with that in the PMV model.

Substituting the data from the yearlong field survey in

Conclusions

The perception of comfort is not a fixed condition according to the point of view of adaptive thermal comfort, whereas it depends on both physiological and non-physiological factors, in particular in free-running buildings. When adaptive opportunities are available and effective, occupants will be able to achieve/improve thermal comfort in terms of psychological and behavioural adaptation.

This paper has developed an Adaptive Predicted Mean Vote (aPMV) model using the “Black Box” method which

Acknowledgement

The authors would like to thank the support from the project nCUBUS - Network for China-UK Urban and Building Sustainability funded by the UK Engineering and Physical Sciences Research Council (EPSRC EP/E040748/1), project “Key Technologies on Control and Improvement of Building Indoor Thermal Environment” (2006BAJ02A09) funded by the Chinese Ministry of Science and Technology under the Chinese Key R&D National 11th Five-Year Plan programme and the project “Theories and methods of dynamic

References (37)

  • M.A. Humphreys

    Outdoor temperatures and comfort indoors

    Building Research and Practice

    (1978)
  • ISO 7730

    Moderate thermal environment, determination of PMV and PPD indices and specification of the condition for thermal comfort

    (1994)
  • Thermal environmental conditions for human occupancy. American Society of Heating, Refrigerating and Air-conditioning...
  • G.S. Brager et al.

    Thermal adaptation in the built environment: a literature review

    Energy and Buildings

    (1998)
  • A. Auliciems

    Towards a psychophysiological model of thermal perception

    International Journal of Biometeorology

    (1981)
  • F. Nicol

    Thermal comfort and temperature standards in Pakistan

  • A. Auliciems et al.

    Air conditioning in Australia I: human thermal factors

    Architectural Science Review

    (1986)
  • J.F. Nicol

    Thermal comfort and temperature standards in Pakistan

  • Cited by (0)

    1

    Runming Yao is a Guest Professor of Chongqing University, China.

    View full text