Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm
Thermal analysis of heat-generating battery pack cooled by several coolants is analyzed numerically. The coolant used is gases, oils, thermal oils, nanofluids, and liquid metals to find the best coolant for temperature distribution. The conductivity ratio between the battery and coolant, flow Reynol...
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2020
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Online Access: | http://irep.iium.edu.my/85261/1/85261_Optimization%20and%20analysis%20of%20maximum%20temperature.pdf http://irep.iium.edu.my/85261/ https://www.tandfonline.com/doi/abs/10.1080/10407782.2020.1845560?journalCode=unht20 https://doi.org/10.1080/10407782.2020.1845560 |
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my.iium.irep.852612020-12-01T06:32:16Z http://irep.iium.edu.my/85261/ Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm Afzal, Asif Mokashi, Imran Khan, Sher Afghan Abdullah, Nur Azam Azami, Muhammad Hanafi TL Motor vehicles. Aeronautics. Astronautics TL1 Motor vehicles Thermal analysis of heat-generating battery pack cooled by several coolants is analyzed numerically. The coolant used is gases, oils, thermal oils, nanofluids, and liquid metals to find the best coolant for temperature distribution. The conductivity ratio between the battery and coolant, flow Reynolds number, and heat generation inside the pack are varied for each coolant. The axial temperature variation, which provides the location and magnitude of maximum temperature, is studied. The maximum temperature of the battery pack is analyzed using response surface methodology, optimization of maximum temperature is performed using particle swarm optimization algorithm, and regression analysis is carried out at the end of this work. The thermal analysis carried out reveals that the gas coolants are inefficient in providing lower temperatures while nanofluids are the most suitable. The response surface reveals that the maximum temperature behavior is different for each category of coolant. Taylor and Francis 2020-11-22 Article PeerReviewed application/pdf en http://irep.iium.edu.my/85261/1/85261_Optimization%20and%20analysis%20of%20maximum%20temperature.pdf Afzal, Asif and Mokashi, Imran and Khan, Sher Afghan and Abdullah, Nur Azam and Azami, Muhammad Hanafi (2020) Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm. Numerical Heat Transfer, Part A: Applications. ISSN 1521-0634 E-ISSN 1040-7782 (In Press) https://www.tandfonline.com/doi/abs/10.1080/10407782.2020.1845560?journalCode=unht20 https://doi.org/10.1080/10407782.2020.1845560 |
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TL Motor vehicles. Aeronautics. Astronautics TL1 Motor vehicles Afzal, Asif Mokashi, Imran Khan, Sher Afghan Abdullah, Nur Azam Azami, Muhammad Hanafi Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
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Thermal analysis of heat-generating battery pack cooled by several coolants is analyzed numerically. The coolant used is gases, oils, thermal oils, nanofluids, and liquid metals to find the best coolant for temperature distribution. The conductivity ratio between the battery and coolant, flow Reynolds number, and heat generation inside the pack are varied for each coolant. The axial temperature variation, which provides the location and magnitude of maximum
temperature, is studied. The maximum temperature of the battery pack is analyzed using response surface methodology, optimization of maximum temperature is performed using particle swarm optimization algorithm,
and regression analysis is carried out at the end of this work. The thermal analysis carried out reveals that the gas coolants are inefficient in providing lower temperatures while nanofluids are the most suitable. The response surface
reveals that the maximum temperature behavior is different for each category of coolant. |
format |
Article |
author |
Afzal, Asif Mokashi, Imran Khan, Sher Afghan Abdullah, Nur Azam Azami, Muhammad Hanafi |
author_facet |
Afzal, Asif Mokashi, Imran Khan, Sher Afghan Abdullah, Nur Azam Azami, Muhammad Hanafi |
author_sort |
Afzal, Asif |
title |
Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
title_short |
Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
title_full |
Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
title_fullStr |
Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
title_full_unstemmed |
Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
title_sort |
optimization and analysis of maximum temperature in a battery pack affected by low to high prandtl number coolants using response surface methodology and particle swarm optimization algorithm |
publisher |
Taylor and Francis |
publishDate |
2020 |
url |
http://irep.iium.edu.my/85261/1/85261_Optimization%20and%20analysis%20of%20maximum%20temperature.pdf http://irep.iium.edu.my/85261/ https://www.tandfonline.com/doi/abs/10.1080/10407782.2020.1845560?journalCode=unht20 https://doi.org/10.1080/10407782.2020.1845560 |
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