中文摘要：

针对预测平均投票数（predicted mean vote,PMV）值在舒适区和节能区之间周期性交替变化的控制方法,提出了基于PMV的动态舒适度冷/热抱怨模型和能耗模型.基于此模型,根据用户设定的舒适和节能两者的协调关系,运用改进的多目标离散粒子群优化算法,得出动态舒适度控制系统输入参数的寻优方法.该方法只需实时测量热环境和居住者热感觉数据,不需建立热环境物理解析模型,普适性强.实验证明了上述控制方法的有效性,该方法可实现动态舒适度的最优控制.

英文摘要：

A PMV （predicted mean vote）-based dynamic thermal comfort （cool/hot） complaint event model and an energy consumption model are proposed for the control method in which PMV values change alternatively between comfortable and energy-saving zones. An improved multi-objective algorithm based on discrete PSO （particle swarm optimization） is applied to calculating optimal values of parameters in dynamic comfort control system according to the balance （specified by users） between comfort and energy conservation. This method only needs to measure data of thermal environment and occupant＇s thermal sensation, without building the physical analytic model. Experiment results demonstrate the effectiveness of the proposed control method. In addition, the realizability of the optimal control to dynamic comfort is also verified.