Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer
Abstract
Electric clothes dryers consume about 6% of US residential electricity consumption. Using a solid-state technology without refrigerant, thermoelectric (TE) heat pump dryers have the potential to be more efficient than units based on electric resistance and less expensive than units based on vapor compression. This study presents a steady state TE dryer model, and validates the model against results from an experimental prototype. The system model is composed of a TE heat pump element model coupled with a psychrometric dryer sub-model. Experimental results had energy factors (EFs) of up to 2.95 kg of dry cloth per kWh (6.51 lbc/kWh), with a dry time of 159 min. A faster dry time of 96 min was also achieved at an EF of 2.54 kgc/kWh (5.60 lbc/kWh). The model was able to replicate the experimental results within 5% of EF and 5% of dry time values. Finally, the results are used to identify important parameters that affect dryer performance, such as relative humidity of air leaving the drum.
- Authors:
-
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
- OSTI Identifier:
- 1423070
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 217; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 42 ENGINEERING; 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; clothes drying; energy efficiency; thermoelectric; heat pump; thermodynamics; modeling
Citation Formats
Patel, Viral K., Gluesenkamp, Kyle R., Goodman, Dakota, and Gehl, Anthony. Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer. United States: N. p., 2018.
Web. doi:10.1016/j.apenergy.2018.02.055.
Patel, Viral K., Gluesenkamp, Kyle R., Goodman, Dakota, & Gehl, Anthony. Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer. United States. https://doi.org/10.1016/j.apenergy.2018.02.055
Patel, Viral K., Gluesenkamp, Kyle R., Goodman, Dakota, and Gehl, Anthony. Wed .
"Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer". United States. https://doi.org/10.1016/j.apenergy.2018.02.055. https://www.osti.gov/servlets/purl/1423070.
@article{osti_1423070,
title = {Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer},
author = {Patel, Viral K. and Gluesenkamp, Kyle R. and Goodman, Dakota and Gehl, Anthony},
abstractNote = {Electric clothes dryers consume about 6% of US residential electricity consumption. Using a solid-state technology without refrigerant, thermoelectric (TE) heat pump dryers have the potential to be more efficient than units based on electric resistance and less expensive than units based on vapor compression. This study presents a steady state TE dryer model, and validates the model against results from an experimental prototype. The system model is composed of a TE heat pump element model coupled with a psychrometric dryer sub-model. Experimental results had energy factors (EFs) of up to 2.95 kg of dry cloth per kWh (6.51 lbc/kWh), with a dry time of 159 min. A faster dry time of 96 min was also achieved at an EF of 2.54 kgc/kWh (5.60 lbc/kWh). The model was able to replicate the experimental results within 5% of EF and 5% of dry time values. Finally, the results are used to identify important parameters that affect dryer performance, such as relative humidity of air leaving the drum.},
doi = {10.1016/j.apenergy.2018.02.055},
journal = {Applied Energy},
number = ,
volume = 217,
place = {United States},
year = {2018},
month = {2}
}
Web of Science