Liquid desiccant dehumidification systems show significant energy-saving potential in HVAC applications. The dynamic characteristics of a liquid desiccant dehumidifier attract increasing attentions in recent years, which are essential for designing appropriate controllers for it. However, due to the complicate coupling of heat and mass transfer inside the dehumidifier, there are few models have been developed for predicting the dynamic characteristics of a packed liquid desiccant dehumidifier. In this paper, an online model was proposed, which predicted the dynamic response of a packed dehumidifier mainly based on the air outlet humidity ratio rather than the inlet parameters of the dehumidifier. The online model was derived from the heat and mass transfer principle and can be described by an exponential function. The dynamic response can be divided into two stages taking the maximum air outlet humidity ratio changing rate as a dividing point. The two unknown parameters (the maximum air outlet humidity ratio changing rate and the time coefficient) in the online model were determined by the first stage of dynamic response, and then the online model predicted the dynamic response of the packed dehumidifier at the second stage. The online model agreed well with the experimental data, casting a new light on learning the internal relation of the dynamic processes of a packed dehumidifier. Furthermore, the relation between the variation of inlets and dynamic response of air outlet humidity ratio could be predicted quickly using the proposed model, contributing to control algorithm development. And a preliminary idea about how to construct an appropriate controller based on the proposed model is presented, which provides a reference for further study.

液体干燥剂除湿系统在HVAC应用中显示出巨大的节能潜力。液体干燥剂除湿机的动态特性近年来受到越来越多的关注，这对于为其设计合适的控制器至关重要。然而，由于除湿机内部传热和传质的复杂耦合，很少有模型可以预测填充式液体除湿机的动态特性。本文提出了一种在线模型，该模型主要根据出风口的湿度比而不是除湿机的入口参数来预测填充式除湿机的动态响应。在线模型是根据传热和传质原理导出的，可以用指数函数描述。以最大出风口湿度比变化率为分，动态响应可分为两个阶段。通过第一阶段的动态响应确定在线模型中的两个未知参数（最大出风口湿度比变化率和时间系数），然后在线模型预测第二阶段填充式除湿机的动态响应。在线模型与实验数据非常吻合，为学习包装式除湿机动态过程的内部关系提供了新的思路。此外，使用该模型可以快速预测进气口变化与出风口湿度比动态响应之间的关系，有助于控制算法的发展。