Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells
In this work, a numerical optimisation process is applied to improve the fluid dynamical aspect of an innovative direct liquid cooling strategy for lithium-ion–based HEV/EV. First, the thermofluidic numerical model of the battery cell defined by means of CFD computational tools was validated with ex...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/13/8/149 |
| _version_ | 1797407379519700992 |
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| author | Manex Larrañaga-Ezeiza Gorka Vertiz Navarro Igor Galarza Garmendia Peru Fernandez Arroiabe Manex Martinez-Aguirre Joanes Berasategi Arostegui |
| author_facet | Manex Larrañaga-Ezeiza Gorka Vertiz Navarro Igor Galarza Garmendia Peru Fernandez Arroiabe Manex Martinez-Aguirre Joanes Berasategi Arostegui |
| author_sort | Manex Larrañaga-Ezeiza |
| collection | DOAJ |
| description | In this work, a numerical optimisation process is applied to improve the fluid dynamical aspect of an innovative direct liquid cooling strategy for lithium-ion–based HEV/EV. First, the thermofluidic numerical model of the battery cell defined by means of CFD computational tools was validated with experimental tests. Then, a comparison between different flow patterns was developed to analyse the influence of the fluid distribution geometry. Finally, a parametric multi-objective optimisation process was implemented arranged by a two-level full factorial design. Considering as input variables the height of the fluid, the number of cooling channels, the number of distributors, and the flow rate, the optimal relationship between the thermal performance of the battery cell, the volumetric energy density of the system, and the power consumption of the strategy was obtained. As a result, the energy density of the system was maximised, and the power consumption was reduced while keeping the cell temperature within the optimal range. |
| first_indexed | 2024-03-09T03:40:33Z |
| format | Article |
| id | doaj.art-8c70b70fd5fa4f2dba26fb234723880b |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-09T03:40:33Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-8c70b70fd5fa4f2dba26fb234723880b2023-12-03T14:41:21ZengMDPI AGWorld Electric Vehicle Journal2032-66532022-08-0113814910.3390/wevj13080149Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery CellsManex Larrañaga-Ezeiza0Gorka Vertiz Navarro1Igor Galarza Garmendia2Peru Fernandez Arroiabe3Manex Martinez-Aguirre4Joanes Berasategi Arostegui5CIDETEC, Basque Research and Technology Alliance (BRTA), Po. Miramón 196, 20014 Donostia-San Sebastián, SpainCIDETEC, Basque Research and Technology Alliance (BRTA), Po. Miramón 196, 20014 Donostia-San Sebastián, SpainCIDETEC, Basque Research and Technology Alliance (BRTA), Po. Miramón 196, 20014 Donostia-San Sebastián, SpainMechanical and Industrial Production Department, Faculty of Engineering, Mondragon Unibersitatea, Loramendi 4, 20500 Arrasate-Mondragón, SpainMechanical and Industrial Production Department, Faculty of Engineering, Mondragon Unibersitatea, Loramendi 4, 20500 Arrasate-Mondragón, SpainMechanical and Industrial Production Department, Faculty of Engineering, Mondragon Unibersitatea, Loramendi 4, 20500 Arrasate-Mondragón, SpainIn this work, a numerical optimisation process is applied to improve the fluid dynamical aspect of an innovative direct liquid cooling strategy for lithium-ion–based HEV/EV. First, the thermofluidic numerical model of the battery cell defined by means of CFD computational tools was validated with experimental tests. Then, a comparison between different flow patterns was developed to analyse the influence of the fluid distribution geometry. Finally, a parametric multi-objective optimisation process was implemented arranged by a two-level full factorial design. Considering as input variables the height of the fluid, the number of cooling channels, the number of distributors, and the flow rate, the optimal relationship between the thermal performance of the battery cell, the volumetric energy density of the system, and the power consumption of the strategy was obtained. As a result, the energy density of the system was maximised, and the power consumption was reduced while keeping the cell temperature within the optimal range.https://www.mdpi.com/2032-6653/13/8/149lithium-ionbatterythermal managementCFDdirect liquid coolingenergy density |
| spellingShingle | Manex Larrañaga-Ezeiza Gorka Vertiz Navarro Igor Galarza Garmendia Peru Fernandez Arroiabe Manex Martinez-Aguirre Joanes Berasategi Arostegui Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells World Electric Vehicle Journal lithium-ion battery thermal management CFD direct liquid cooling energy density |
| title | Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells |
| title_full | Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells |
| title_fullStr | Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells |
| title_full_unstemmed | Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells |
| title_short | Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells |
| title_sort | parametric optimisation of a direct liquid cooling based prototype for electric vehicles focused on pouch type battery cells |
| topic | lithium-ion battery thermal management CFD direct liquid cooling energy density |
| url | https://www.mdpi.com/2032-6653/13/8/149 |
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