Reducing Air-Conditioning System Energy Using a PMV Index

dc.creator	Li, H.
dc.creator	Zhang, Q.
dc.date.accessioned	2007-05-07T20:45:46Z
dc.date.available	2007-05-07T20:45:46Z
dc.date.issued	2006
dc.identifier.other	ESL-IC-06-11-16
dc.identifier.uri	https://hdl.handle.net/1969.1/5314
dc.description.abstract	The control system of central air-conditioning, based on PMV, not only improves thermal comfort but also reduces system energy consumption. A new thermal comfort degree softsensor model is built via use of the CMAC neural network nonlinear calibration function. It can realize on-line detection of thermal comfort. At the same time it can also realize real-time control of central air-conditioning system based on PMV. Simulation results demonstrate the simplicity and effectiveness of the presented method.	en
dc.format.extent	182172 bytes	en
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.publisher	Energy Systems Laboratory (http://esl.tamu.edu)
dc.publisher	Texas A&M University (http://www.tamu.edu)
dc.subject	PMV	en
dc.subject	CMAC neural network	en
dc.subject	Thermal comfort degree	en
dc.title	Reducing Air-Conditioning System Energy Using a PMV Index	en