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Title: 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:
 [1];  [1];  [1];  [1]
  1. 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 = {Wed Feb 28 00:00:00 EST 2018},
month = {Wed Feb 28 00:00:00 EST 2018}
}

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