{"title":"A revised PMV model: From a physiological standpoint","authors":"Lianfei Zhuang, Jingxin Huang, Ke Zhong","doi":"10.1177/01436244231191244","DOIUrl":null,"url":null,"abstract":"In the field of thermal comfort, the adaptive approach is widely used. However, the current main adaptive models correlate thermal comfort with outdoor temperature, and the PMV model is only concerned with behavioural adaptation. The purpose of this paper is to develop a revised PMV (rPMV) model that can account for both behavioural and psychological adaptation. From a physiological standpoint, psychological adaptation affects the actual neutral skin temperature and actual sensitivity to thermal load change, whereas these two parameters used in the PMV model have no relation to psychological adaptation. When using the actual neutral skin temperature and actual sensitivity to thermal load change, the rPMV model can thus account for both psychological and behavioural adaptation. The actual neutral skin temperatures and sensitivities for Shanghai residents in the autumn, as well as Nanjing residents in the summer and winter, were calculated using data from field experiments that measured environmental parameters and investigated thermal sensation. The results show that the rPMV model significantly improves thermal sensation prediction accuracy compared to the PMV model. According to the findings, the rPMV model can be used to create an energy-efficient and comfortable indoor environment. Practical applications: The thermal comfort prediction model assesses indoor climate, which has a significant impact on building energy consumption and thus its sustainability. The use of a good prediction model is critical to the success of building design. This paper develops a thermal comfort prediction model that can not only accurately predict thermal comfort of building occupant but also be used to design sustainable buildings.","PeriodicalId":50724,"journal":{"name":"Building Services Engineering Research & Technology","volume":"44 1","pages":"557 - 575"},"PeriodicalIF":1.5000,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Building Services Engineering Research & Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/01436244231191244","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of thermal comfort, the adaptive approach is widely used. However, the current main adaptive models correlate thermal comfort with outdoor temperature, and the PMV model is only concerned with behavioural adaptation. The purpose of this paper is to develop a revised PMV (rPMV) model that can account for both behavioural and psychological adaptation. From a physiological standpoint, psychological adaptation affects the actual neutral skin temperature and actual sensitivity to thermal load change, whereas these two parameters used in the PMV model have no relation to psychological adaptation. When using the actual neutral skin temperature and actual sensitivity to thermal load change, the rPMV model can thus account for both psychological and behavioural adaptation. The actual neutral skin temperatures and sensitivities for Shanghai residents in the autumn, as well as Nanjing residents in the summer and winter, were calculated using data from field experiments that measured environmental parameters and investigated thermal sensation. The results show that the rPMV model significantly improves thermal sensation prediction accuracy compared to the PMV model. According to the findings, the rPMV model can be used to create an energy-efficient and comfortable indoor environment. Practical applications: The thermal comfort prediction model assesses indoor climate, which has a significant impact on building energy consumption and thus its sustainability. The use of a good prediction model is critical to the success of building design. This paper develops a thermal comfort prediction model that can not only accurately predict thermal comfort of building occupant but also be used to design sustainable buildings.
期刊介绍:
Building Services Engineering Research & Technology is one of the foremost, international peer reviewed journals that publishes the highest quality original research relevant to today’s Built Environment. Published in conjunction with CIBSE, this impressive journal reports on the latest research providing you with an invaluable guide to recent developments in the field.