基于改进PMV-PPD模型的北京地铁车站公共区环境舒适性评价及预测  

Environmental Comfort Evaluation and Prediction of Beijing Metro Station Public Area Based on Improved PMV-PPD Model

作　　者：张无垠 盛旭高 毛军[2] 赵明珠 祝瑞男 刘正 ZHANG Wu-yin;SHENG Xu-gao;MAO Jun;ZHAO Ming-zhu;ZHU Rui-nan;LIU Zheng(Electromechanical Branch of Beijing Metro Operation Co.,Ltd.,Beijing 100040,China;Beijing Jiaotong University,Beijing 100044,China;Aerospace Macro Information Technology Beijing Co.,Ltd.,Beijing 100044,China)

机构地区：[1]北京市地铁运营有限公司,北京100040 [2]北京交通大学土木建筑工程学院,北京100044 [3]航天宏图信息科技北京有限公司,北京100044

出　　处：《科学技术与工程》2025年第9期3851-3860,共10页Science Technology and Engineering

基　　金：北京市地铁运营有限公司科技项目(JC2022WN-03,C22GY00210);国家自然科学基金(52172336)。

摘　　要：地铁车站环境舒适性问题通常采用预计平均热感觉指数(predicted mean vote,PMV)及预计不满意百分数(predicted percent dissatisfied,PPD)进行分析,基于PMV-PPD舒适性指标计算模型,研究不同环境参数对舒适度的权重占比,考虑乘客衣着状态及运动状态的时空特性,改进PMV计算模型,考虑环境温度剧烈变化对舒适度的影响,改进PPD计算模型,并基于改进的PMV-PPD计算模型研究车站公共区的环境舒适性。在此基础上,采用长短期记忆(long short-term memory,LSTM)神经网络,对环境舒适度进行预测,研究预测方法的可行性。研究结果表明:新陈代谢率、空气温度、服装热阻、相对湿度对环境舒适度的权重占比分别为0.558、0.260、0.113、0.069;时间一定时,站台不同监测点处的PMV、PPD的最大差值分别约为15%、60%;改进后的PMV-PPD计算模型相对于传统的PMV-PPD计算模型更具有普适性;神经网络可以较好地对PMV及PPD值进行预测,PMV实际值与预测值的最大误差为8%,PPD实际值与预测值的最大误差为14%。The issue of comfort in subway stations is typically analyzed using the predicted mean vote(PMV)and the predicted percent dissatisfied(PPD)indices.Based on the PMV-PPD comfort indices calculation model,the weight proportions of different environmental parameters on comfort were studied.The PMV calculation model was improved by considering the spatiotemporal characteristics of passengers'clothing and activity levels.The PPD calculation model was enhanced by taking into account the impact of drastic environmental temperature changes on comfort.The environmental comfort of public areas in stations was then analyzed using the improved PMV-PPD calculation model.On this basis,the feasibility of predicting environmental comfort using long short-term memory(LSTM)networks was explored.The research results indicate that the weight proportions of metabolic rate,air temperature,clothing thermal resistance,and humidity on environmental comfort are 0.558,0.260,0.113,and 0.069,respectively.At a given time,the maximum differences in PMV and PPD at different monitoring points on the platform are approximately 15%and 60%,respectively.The improved PMV-PPD calculation model is found to be more universally applicable compared to the traditional PMV-PPD calculation model.The neural network is shown to accurately predict PMV and PPD values,with a maximum error of 8%for PMV and 14%for PPD between the actual and predicted values.

关 键 词：站台 PMV PPD 权重 神经网络 

分 类 号：TU831.3[建筑科学—供热、供燃气、通风及空调工程]