Intelligent temperature control method and system based on human body heat sensation

Abstract

The invention discloses an intelligent temperature control system and method based on human body heat sensation. The method comprises the steps that according to user preset information and indoor and outdoor air temperature historical data, a comprehensive heat experience temperature value is quantified; and according to the heat experience temperature value, a CaPMV model value is calculated; and according to the CaPMV model value, the indoor temperature is regulated and controlled. According to the intelligent temperature control system and method, the quantitative indexes and methods of natural ventilation heat experience, heating air conditioner heat experience and outdoor air temperature heat experience are comprehensively considered, the defect that an existing intelligent control air conditioner system based on the PMV index only considers objective thermophysical parameters and does not consider the influence of crowd heat experience is overcome, the heating air conditioner heat environment comfort under the crowd diversified heat experience condition can be evaluated more accurately, and a scientific basis is provided for control over heating air conditioner systems with distributed and intermittent characteristics in areas with hot summer, cold winter and the like.

Description

technical field [0001] The invention relates to the technical field of air conditioner temperature control, in particular to an intelligent air conditioner temperature control method and system based on human thermal sensation. Background technique [0002] Since modern humans spend most of their time indoors, the thermal comfort level of a building is closely related to people's living and working conditions. The thermal comfort of the human body is not only affected by temperature, but also by other factors such as humidity, wind speed, and radiant temperature. Therefore, as early as around 1960, Fanger proposed the PMV (Predicted Mean Vote) index model, which was used to predict the thermal comfort level of the average population based on physical parameters such as the thermal environment. Building Control Systems. Due to the diversity of indoor and outdoor thermal environments in different climate zones and seasons, people living in an environment with different therm...

AI Technical Summary

Problems solved by technology

[0003] Traditional indoor temperature intelligent control methods based on thermal sensation prediction, such as PMV indicators, do not consider the influence of human thermal experience factors, and are only suitable for thermal comfort evaluation and temperature control in central cooling and heating environments.

Although the existing adaptive thermal comfort model method considers the thermal experience of the human body, it only evaluates and regulates the indoor temperature based on the outdoor temperature value, without considering the influence of the thermal experience of indoor heating and air conditioning, and is only suitable for the thermal environment evaluation of naturally ventilated buildings.

For non-centralized heating and air-conditioning environments, the thermal experience of the human body is varied due to the influence of indoor and outdoor diverse thermal environments, but the existing technology still lacks accurate thermal comfort evaluation and system control methods for this

Specifically, for people with different heating, air-conditioning and outdoor comprehensive thermal experiences, the current technology lacks scientific quantification methods of human thermal experience, and corresponding indoor cooling and heating control system products and control methods based on quantified values ​​of human thermal experience.

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