Office occupants spend most of their time in an enclosed indoor environment, controlled by heating, ventilation and air-conditioning (HVAC) systems especially in subtropical regions owing to the hot and humid climate. A reasonable indoor environment evaluation model is necessary to achieve the reliable control of HVAC systems that satisfies the occupants’ health and comfort needs. However, traditional HVAC systems are controlled based on a simple index that does not consider the synthesis of indoor air quality, thermal comfort and occupant preferences. In this paper, we develop a comprehensive evaluation model that encompasses these three aspects based on field survey. Field surveys were conducted to investigate indoor environmental conditions and preferences of the occupants. Collected data were then verified for model hypothesis rationality and reviewed to identify weighting factors using Pearson and regression analysis. Results showed that these parameters had significant correlations without noticeable collinearity and can be integrated using regression method. The weighting factors of each parameter were calculated using occupants’ sensation and expectation to reflect the subjective preferences in model. Finally, an evaluation model expressing the indoor thermal, air quality and occupant preferences was developed to provide an HVAC intelligent control system that is more responsive to occupant needs.

办公室居住者大部分时间都在封闭的室内环境中度过，由供暖、通风和空调 (HVAC) 系统控制，尤其是在气候炎热潮湿的亚热带地区。需要合理的室内环境评价模型来实现对满足居住者健康和舒适需求的暖通空调系统的可靠控制。然而，传统的暖通空调系统是基于一个简单的指标来控制的，没有考虑室内空气质量、热舒适度和居住者偏好的综合。在本文中，我们基于实地调查开发了一个包含这三个方面的综合评价模型。进行了实地调查以调查居住者的室内环境条件和偏好。然后验证收集的数据的模型假设合理性，并使用 Pearson 和回归分析进行审查以识别加权因子。结果表明，这些参数具有显着的相关性，没有明显的共线性，可以使用回归方法进行积分。使用乘员的感觉和期望来计算每个参数的权重因子，以反映模型中的主观偏好。最后，开发了表达室内热、空气质量和居住者偏好的评估模型，以提供更能响应居住者需求的 HVAC 智能控制系统。结果表明，这些参数具有显着的相关性，没有明显的共线性，可以使用回归方法进行积分。使用乘员的感觉和期望来计算每个参数的权重因子，以反映模型中的主观偏好。最后，开发了表达室内热、空气质量和居住者偏好的评估模型，以提供更能响应居住者需求的 HVAC 智能控制系统。结果表明，这些参数具有显着的相关性，没有明显的共线性，可以使用回归方法进行积分。使用乘员的感觉和期望来计算每个参数的权重因子，以反映模型中的主观偏好。最后，开发了表达室内热、空气质量和居住者偏好的评估模型，以提供更能响应居住者需求的 HVAC 智能控制系统。