{"title":"The comparison of particle filter and extended Kalman filter in predicting building envelope heat transfer coefficient","authors":"Xiaoqin Wang, Xiaolong Wang","doi":"10.1109/CCIS.2012.6664639","DOIUrl":null,"url":null,"abstract":"The building envelope heat transfer coefficient is an important measurement of building energy efficiency. The detection of the heat transfer coefficient is always impacted by surrounding environment and noises. Meanwhile it is impractical to accumulate rich enough data as input to calculate the heat transfer coefficient. The Particle Filter (PF) and Extended Kalman Filter(EKF) are employed in this paper in predicting the heat transfer coefficient based on the temperature control box-heat flow model. With the comparison of the two predicted values with the real measured one, the Particle Filter shows high efficiency and better accurate than Extended Kalman Filter. The simulation results show that the accuracy of PF is high. The budget result of PF is more close to the real values. Then the estimated calculation according to Particle Filter is used to calculate wall body heat transfer coefficient.","PeriodicalId":392558,"journal":{"name":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIS.2012.6664639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The building envelope heat transfer coefficient is an important measurement of building energy efficiency. The detection of the heat transfer coefficient is always impacted by surrounding environment and noises. Meanwhile it is impractical to accumulate rich enough data as input to calculate the heat transfer coefficient. The Particle Filter (PF) and Extended Kalman Filter(EKF) are employed in this paper in predicting the heat transfer coefficient based on the temperature control box-heat flow model. With the comparison of the two predicted values with the real measured one, the Particle Filter shows high efficiency and better accurate than Extended Kalman Filter. The simulation results show that the accuracy of PF is high. The budget result of PF is more close to the real values. Then the estimated calculation according to Particle Filter is used to calculate wall body heat transfer coefficient.