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Indoor thermal environment optimal control for thermal comfort and energy saving based on online monitoring of thermal sensation

机译：基于热感在线监测的室内热环境最优控制，可实现热舒适和节能

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The automatic control of Heating, ventilation and Air Conditioning (HVAC) systems aims to achieve the thermal comfort requirements of occupants with minimum energy consumption. The automatic control strategy of existing HVAC systems determines a set value for creating a thermal environment in accordance with relevant design principles and/or occupants' preferences. An overly-cooled indoor environment may reduce the occupant's thermal comfort and result in excessive energy consumption. In order to improve thermal comfort and save energy, this study proposes an indoor thermal environment optimal control method based on the online monitoring of thermal sensation. First, a smart wristband collects the human physiological data, including wrist skin temperature and heart rate. This is for predicting human thermal sensation, where a fuzzy comprehensive evaluation method is employed to determine the integrated thermal sensation of multi occupants. Then, a linear adjustment algorithm is developed to optimize the indoor temperature set point. In order to evaluate the performance of the thermal sensation based control method, a series of experiments were conducted using the thermal sensation-based control and set point-based control. The results show that the thermal sensation-based control can adjust the temperature setting in a timely fashion according to the occupants' integrated thermal sensations, although they do not necessarily state their subjective perception. It is also revealed that the thermal sensation-based control can achieve a more comfortable thermal environment than the set point-based control. Furthermore, the thermal sensation-based control saves 13.8% in daily energy consumption compared to the set point-based control method. (C) 2019 Elsevier B.V. All rights reserved.
机译：加热，通风和空调（HVAC）系统的自动控制旨在以最小的能耗实现乘员的热舒适性要求。现有HVAC系统的自动控制策略根据相关的设计原则和/或居住者的喜好确定用于创建热环境的设定值。过冷的室内环境可能会降低乘员的热舒适度并导致过多的能量消耗。为了提高热舒适度并节约能源，本研究提出了一种基于热感在线监测的室内热环境最优控制方法。首先，智能腕带会收集人体生理数据，包括腕部皮肤温度和心率。这是用于预测人类的热感，其中采用模糊综合评估方法来确定多人的综合热感。然后，开发了线性调整算法来优化室内温度设定点。为了评估基于热感觉的控制方法的性能，使用基于热感觉的控制和基于设定点的控制进行了一系列实验。结果表明，基于热感的控件可以根据乘员的综合热感及时调整温度设置，尽管他们不一定会陈述他们的主观感觉。还揭示出，基于热感觉的控制比基于设定点的控制可实现更舒适的热环境。此外，与基于设定点的控制方法相比，基于热感觉的控制可节省每日能源消耗的13.8％。 （C）2019 Elsevier B.V.保留所有权利。

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