Thermal adaptations, as feedbacks of occupants to physical stimuli, extend thermal comfort zone thereby reducing building energy consumption effectively. The rational approach models thermal comfort from the perspective of the body's heat balance, but is limited in explaining the thermal adaptations. The adaptive approach of modeling thermal comfort can fully account for the thermal adaptations, but ignores the body's heat balance. To improve thermal comfort prediction, this study proposes an adaptive‐rational thermal comfort model, that is, an adaptive predicted mean vote with a variable adaptive coefficient (termed as arPMV). By linearly linking the negative feedback effects of the thermal adaptations to the ambient temperature according to the adaptive approach, the variable adaptive coefficient is linearly related to the reciprocal of the ambient temperature with two constants. The variable adaptive coefficient is determined by explicitly quantifying the two constants as the functions of the predicted mean vote, thermal sensation vote, and ambient temperature. The proposed arPMV is validated for naturally ventilated, air‐conditioned, and mixed‐mode buildings, with the mean absolute error and the robustness of the thermal sensation prediction reduced by 24.8%‐83.5% and improved by 49.7%‐83.4%, respectively.

中文翻译：

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自适应理性热舒适模型：具有可变自适应系数的自适应预测均值投票。

作为乘员对身体刺激的反馈，热适应扩展了热舒适区，从而有效降低了建筑能耗。理性的方法从身体的热量平衡角度模拟热舒适性，但是在解释热量适应方面受到限制。对热舒适性进行建模的自适应方法可以完全考虑热适应问题，但忽略了人体的热量平衡。为了改善热舒适性预测，本研究提出了一种自适应有理量的热舒适性模型，即具有可变自适应系数（称为arPMV）的自适应预测平均投票。通过根据自适应方法将热适应的负反馈效应与环境温度线性关联，可变的自适应系数与环境温度的倒数线性相关，具有两个常数。通过将两个常数明确量化为预测的平均投票，热感觉投票和环境温度的函数，可以确定可变的自适应系数。拟议的arPMV已针对自然通风，空调和混合模式建筑进行了验证，平均绝对误差和热感预测的稳健性分别降低了24.8％-83.5％和提高了49.7％-83.4％。