Journal article
An Evaluation of Classical Steady-State Off-Line Linear Parameter Estimation Methods Applied to Chiller Performance Data
HVAC&R research, v 8(1), pp 101-124
01 Jan 2002
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The objective of this paper is to evaluate different inverse methods with application to off-line model parameter estimation using data from a field-operated chiller. In HVAC&R data analysis, there is sometimes a need to evaluate and use estimation techniques that are more subtle than the ordinary least square (OLS) method. One example is in fault detection and diagnosis of HVAC&R equipment and systems using performance data obtained from field monitoring. By identifying a better performance model, the fault detection process is more likely to be refined and accurate. In this paper a number of exploratory, diagnostic, and classical estimation methods are reviewed to determine the circumstances in which they are likely to be superior to the OLS method. These methods are then evaluated using monitored data from a field-operated chiller. This study provides a reference on parameter estimation methods for the HVAC&R community.
Metrics
Details
- Title
- An Evaluation of Classical Steady-State Off-Line Linear Parameter Estimation Methods Applied to Chiller Performance Data
- Creators
- T. Agami Reddy - Department of Civil and Architectural Engineering , Drexel UniversityKlaus K. Andersen - Technical University of Denmark
- Publication Details
- HVAC&R research, v 8(1), pp 101-124
- Publisher
- Taylor & Francis Group
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:000173379900005
- Scopus ID
- 2-s2.0-0036165722
- Other Identifier
- 991019184826704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Construction & Building Technology
- Engineering, Mechanical
- Thermodynamics