Development of a Computational Fluid Dynamics Simulation Framework for Aerothermal Analyses of Electric Vehicle Battery PacksSource: Journal of Electrochemical Energy Conversion and Storage:;2023:;volume( 021 ):;issue: 003::page 31009-1DOI: 10.1115/1.4063800Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The rise of electric vehicles has driven the extensive adoption of lithium-ion batteries (LIBs) due to their favorable attributes—compactness, low resistance, high power density, and minimal self-discharge. To enhance LIB reliability, an efficient battery thermal management system is imperative. This paper introduces a finite volume-based aerothermal analysis framework for a 32-cell high-energy density LIB pack. We also explore the effectiveness of various turbulence models in capturing local hotspots, discharge rates, and current levels across different geometries and inlet velocities. Our approach involves modeling the battery using Simcenter Battery Design Studio and importing it into Simcenter star-ccm+ for aerothermal simulations in which temperature distribution, discharge rates, current levels, and maximum temperature across are monitored for aligned, cross, and staggered configurations of the battery pack under varying inlet velocities. Our findings highlight the significant impact of boundary condition modeling on simulation stability. Also we observed that the standard k–ε model provides the most accurate predictions, with prediction accuracy within 3–10% of experimental data. Moreover, we identify substantial dependencies between heat generation and discharge current, as well as thermal gradients and inlet velocity. Finally, we conclude that the aligned cell arrangement offers the best thermal uniformity and cooling efficiency.
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contributor author | Misar, Adit | |
contributor author | Jain, Ayushi | |
contributor author | Xu, Jun | |
contributor author | Uddin, Mesbah | |
date accessioned | 2024-12-24T19:04:14Z | |
date available | 2024-12-24T19:04:14Z | |
date copyright | 11/8/2023 12:00:00 AM | |
date issued | 2023 | |
identifier issn | 2381-6872 | |
identifier other | jeecs_21_3_031009.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4303233 | |
description abstract | The rise of electric vehicles has driven the extensive adoption of lithium-ion batteries (LIBs) due to their favorable attributes—compactness, low resistance, high power density, and minimal self-discharge. To enhance LIB reliability, an efficient battery thermal management system is imperative. This paper introduces a finite volume-based aerothermal analysis framework for a 32-cell high-energy density LIB pack. We also explore the effectiveness of various turbulence models in capturing local hotspots, discharge rates, and current levels across different geometries and inlet velocities. Our approach involves modeling the battery using Simcenter Battery Design Studio and importing it into Simcenter star-ccm+ for aerothermal simulations in which temperature distribution, discharge rates, current levels, and maximum temperature across are monitored for aligned, cross, and staggered configurations of the battery pack under varying inlet velocities. Our findings highlight the significant impact of boundary condition modeling on simulation stability. Also we observed that the standard k–ε model provides the most accurate predictions, with prediction accuracy within 3–10% of experimental data. Moreover, we identify substantial dependencies between heat generation and discharge current, as well as thermal gradients and inlet velocity. Finally, we conclude that the aligned cell arrangement offers the best thermal uniformity and cooling efficiency. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Development of a Computational Fluid Dynamics Simulation Framework for Aerothermal Analyses of Electric Vehicle Battery Packs | |
type | Journal Paper | |
journal volume | 21 | |
journal issue | 3 | |
journal title | Journal of Electrochemical Energy Conversion and Storage | |
identifier doi | 10.1115/1.4063800 | |
journal fristpage | 31009-1 | |
journal lastpage | 31009-12 | |
page | 12 | |
tree | Journal of Electrochemical Energy Conversion and Storage:;2023:;volume( 021 ):;issue: 003 | |
contenttype | Fulltext |