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A review of thermal comfort models and indicators for indoor environments

机译：室内环境热舒适性模型和指标综述

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摘要

This paper reviews the most used thermal comfort models and indicators with their variants, discussing their usage in control problems referring to energy management in indoor applications. The first part addresses the recent literature referring to the thermal comfort concepts, models of human thermal comfort, thermal comfort models and indicators, thermal comfort standards, control systems, optimisation methods, and practical assessments. Then, the ambient and personal parameters used to represent thermal comfort and thermal sensation are recalled. The following part reviews the definitions and usage of a number of thermal comfort indices, mainly related to the Predicted Mean Vote (PMV), the Actual Mean Vote (AMV), and the Predicted Percentage Dissatisfied (PPD), with their modifications and variants, indicating a number of applications to different situations in indoor environments. The last part reviews the thermal comfort models used to define control strategies in indoor applications, discussing the characteristics and parameters of models based on artificial neural networks, autoregressive variants, fuzzy control, and hybrid models combining different approaches. The characteristics of these models and their usage to predict the indoor air temperature and the PMV index are discussed with reference to the identification of the several inputs used in relevant literature contributions.
机译：本文回顾了最常用的热舒适模型和指示器及其变型，并讨论了它们在控制问题中的使用，涉及室内应用中的能源管理。第一部分介绍了有关热舒适性概念，人体热舒适性模型，热舒适性模型和指标，热舒适性标准，控制系统，优化方法和实际评估的最新文献。然后，调出用于表示热舒适性和热感的环境和个人参数。以下部分回顾了一些热舒适指数的定义和用法，主要涉及预测平均投票（PMV），实际平均投票（AMV）和预测不满意百分比（PPD）及其修改和变化，指示在室内环境中针对不同情况的多种应用。最后一部分回顾了用于定义室内应用控制策略的热舒适模型，讨论了基于人工神经网络，自回归变量，模糊控制以及结合了不同方法的混合模型的模型的特征和参数。这些模型的特性及其在预测室内空气温度和PMV指数中的用途将参考相关文献中使用的几种输入的识别进行讨论。

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