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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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor and Francis
2020
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Subjects: | |
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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Summary: | 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. |
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