Mahmood, A. orcid.org/0000-0002-0858-9003, Cockerill, T., de Boer, G. orcid.org/0000-0002-5647-1771 et al. (2 more authors) (Cover date: September-2 2024) Heat Transfer Modeling and Optimal Thermal Management of Electric Vehicle Battery Systems. Energies, 17 (18). 4575. ISSN 1996-1073
Abstract
<jats:p>Lithium ion (Li-ion) battery packs have become the most popular option for powering electric vehicles (EVs). However, they have certain drawbacks, such as high temperatures and potential safety concerns as a result of chemical reactions that occur during their charging and discharging processes. These can cause thermal runaway and sudden deterioration, and therefore, efficient thermal management systems are essential to boost battery life span and overall performance. An electrochemical-thermal (ECT) model for Li-ion batteries and a conjugate heat transfer model for three-dimensional (3D) fluid flow and heat transfer are developed using COMSOL Multiphysics®. These are used within a novel computational fluid dynamics (CFD)-enabled multi-objective optimization approach, which is used to explore the effect of the mini-channel cold plates’ geometrical parameters on key performance metrics (battery maximum temperature (Tmax), pressure drop (∆P), and temperature standard deviation (Tσ)). The performance of two machine learning (ML) surrogate methods, radial basis functions (RBFs) and Gaussian process (GP), is compared. The results indicate that the GP ML approach is the most effective. Global minima for the maximum temperature, temperature standard deviation, and pressure drop (Tmax, Tσ, and ∆P, respectively) are identified using single objective optimization. The third version of the generalized differential evaluation (GDE3) algorithm is then used along with the GP surrogate models to perform multi-objective design optimization (MODO). Pareto fronts are generated to demonstrate the potential trade-offs between Tmax, Tσ, and ∆P. The obtained optimization results show that the maximum temperature dropped from 36.38 to 35.98 °C, the pressure drop dramatically decreased from 782.82 to 487.16 Pa, and the temperature standard deviation decreased from 2.14 to 2.12 K; the corresponding optimum design parameters are the channel width of 8 mm and the horizontal spacing near the cold plate margin of 5 mm.</jats:p>
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Sep 2024 08:56 |
Last Modified: | 18 Sep 2024 08:56 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/en17184575 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:217281 |