Framework for rapid design and optimisation of immersive battery cooling system
<p dir="ltr">Effective battery thermal management system (BTMS) is critical for lithium-ion battery (LIB) safety and performance in electric vehicles. This study presents a CFD-driven optimisation framework for an immersion cooling BTMS using sustainable palm biodiesel as coolant. Th...
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2025
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| _version_ | 1864513521719443456 |
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| author | Ali Almshahy (23544823) |
| author2 | Z. Khatir (23356891) K. J. Kubiak (23643670) Mansour Al Qubeissi (20931869) |
| author2_role | author author author |
| author_facet | Ali Almshahy (23544823) Z. Khatir (23356891) K. J. Kubiak (23643670) Mansour Al Qubeissi (20931869) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ali Almshahy (23544823) Z. Khatir (23356891) K. J. Kubiak (23643670) Mansour Al Qubeissi (20931869) |
| dc.date.none.fl_str_mv | 2025-11-12T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1007/s00366-025-02228-7 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Framework_for_rapid_design_and_optimisation_of_immersive_battery_cooling_system/31890262 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Environmental engineering Fluid mechanics and thermal engineering Information and computing sciences Artificial intelligence Machine learning Battery thermal management Biodiesel coolant Hybrid electric vehicles Immersion cooling Optimisation Surrogate modelling |
| dc.title.none.fl_str_mv | Framework for rapid design and optimisation of immersive battery cooling system |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Effective battery thermal management system (BTMS) is critical for lithium-ion battery (LIB) safety and performance in electric vehicles. This study presents a CFD-driven optimisation framework for an immersion cooling BTMS using sustainable palm biodiesel as coolant. The Multi-scale Multi-Domain (NTGK) framework is conducted to effectively capture the complex interactions among various physicochemical processes. The Electrochemical-thermal Model (ECM) is applied using the Newman, Tiedeman, Gu, and Kim (NTGK) model. A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. Two key parameters are optimised, namely: battery gap spacing (3–10 mm) and inlet/outlet width (5–15 mm), via Optimal Latin Hypercube Sampling, Support Vector Regression, and GDE3 algorithm. Palm biodiesel is used as a dielectric coolant in the proposed system to preserve LIB temperature within 20–40°C, preventing thermal runaway and ensuring a lightweight BTMS design. Compared to a conventional 3M-Novec, the palm biodiesel achieved system lightweight by 43%. The findings can establish biofuel immersion cooling as an eco-friendly BTMS solution, achieving Pareto-optimal figures: T<sub>max</sub> < 29.9°C, ΔT < 5°C, and ΔP < 145.275 Pa (at 5C and 0.05 m/s).</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Engineering with Computers<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s00366-025-02228-7" target="_blank">https://dx.doi.org/10.1007/s00366-025-02228-7</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7fc0f360f92ae3ef5806f74ae291e177 |
| identifier_str_mv | 10.1007/s00366-025-02228-7 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/31890262 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Framework for rapid design and optimisation of immersive battery cooling systemAli Almshahy (23544823)Z. Khatir (23356891)K. J. Kubiak (23643670)Mansour Al Qubeissi (20931869)EngineeringElectrical engineeringEnvironmental engineeringFluid mechanics and thermal engineeringInformation and computing sciencesArtificial intelligenceMachine learningBattery thermal managementBiodiesel coolantHybrid electric vehiclesImmersion coolingOptimisationSurrogate modelling<p dir="ltr">Effective battery thermal management system (BTMS) is critical for lithium-ion battery (LIB) safety and performance in electric vehicles. This study presents a CFD-driven optimisation framework for an immersion cooling BTMS using sustainable palm biodiesel as coolant. The Multi-scale Multi-Domain (NTGK) framework is conducted to effectively capture the complex interactions among various physicochemical processes. The Electrochemical-thermal Model (ECM) is applied using the Newman, Tiedeman, Gu, and Kim (NTGK) model. A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. Two key parameters are optimised, namely: battery gap spacing (3–10 mm) and inlet/outlet width (5–15 mm), via Optimal Latin Hypercube Sampling, Support Vector Regression, and GDE3 algorithm. Palm biodiesel is used as a dielectric coolant in the proposed system to preserve LIB temperature within 20–40°C, preventing thermal runaway and ensuring a lightweight BTMS design. Compared to a conventional 3M-Novec, the palm biodiesel achieved system lightweight by 43%. The findings can establish biofuel immersion cooling as an eco-friendly BTMS solution, achieving Pareto-optimal figures: T<sub>max</sub> < 29.9°C, ΔT < 5°C, and ΔP < 145.275 Pa (at 5C and 0.05 m/s).</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Engineering with Computers<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s00366-025-02228-7" target="_blank">https://dx.doi.org/10.1007/s00366-025-02228-7</a></p>2025-11-12T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s00366-025-02228-7https://figshare.com/articles/journal_contribution/Framework_for_rapid_design_and_optimisation_of_immersive_battery_cooling_system/31890262CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/318902622025-11-12T03:00:00Z |
| spellingShingle | Framework for rapid design and optimisation of immersive battery cooling system Ali Almshahy (23544823) Engineering Electrical engineering Environmental engineering Fluid mechanics and thermal engineering Information and computing sciences Artificial intelligence Machine learning Battery thermal management Biodiesel coolant Hybrid electric vehicles Immersion cooling Optimisation Surrogate modelling |
| status_str | publishedVersion |
| title | Framework for rapid design and optimisation of immersive battery cooling system |
| title_full | Framework for rapid design and optimisation of immersive battery cooling system |
| title_fullStr | Framework for rapid design and optimisation of immersive battery cooling system |
| title_full_unstemmed | Framework for rapid design and optimisation of immersive battery cooling system |
| title_short | Framework for rapid design and optimisation of immersive battery cooling system |
| title_sort | Framework for rapid design and optimisation of immersive battery cooling system |
| topic | Engineering Electrical engineering Environmental engineering Fluid mechanics and thermal engineering Information and computing sciences Artificial intelligence Machine learning Battery thermal management Biodiesel coolant Hybrid electric vehicles Immersion cooling Optimisation Surrogate modelling |