Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites
Electric vehicles that use lithium ion (Li-Ion) batteries as an alternative to fossil fuels have emerged as a viable solution to the environmental and sustainability problems associated with these fuels. Due to their sensitivity, Li-Ion batteries have been the subject of intense heat management rese...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_02011.pdf |
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| author | Marappan Muthukumar Mahendran A. Ravivarman G. Suresh Kumar K. Elango M. Kesavan S.P. Devarajan R. |
| author_facet | Marappan Muthukumar Mahendran A. Ravivarman G. Suresh Kumar K. Elango M. Kesavan S.P. Devarajan R. |
| author_sort | Marappan Muthukumar |
| collection | DOAJ |
| description | Electric vehicles that use lithium ion (Li-Ion) batteries as an alternative to fossil fuels have emerged as a viable solution to the environmental and sustainability problems associated with these fuels. Due to their sensitivity, Li-Ion batteries have been the subject of intense heat management research for the last ten years. There are a number of ways to regulate the complicated dynamics that cause Li-Ion batteries’ temperatures to rise. This work shows how to optimize the thermal management control variables using design of experiments (DOE), keeping it as the research emphasis. The variables used for optimization include the phase change materials mass denotes as X, the thermal conduction of paraffin aluminum composite denotes as Y, and the water flow rate denotes as Z. Researchers have looked at how these factors affect the rate of heat buildup in Li-Ion batteries. Studying the effect of Li-Ion battery temperature management parameters required a full factorial DOE with two repetitions. In order to evaluate the hypotheses, multivariate analysis made use of analysis of variance (ANOVA). This included controlling for both the 1st and 2nd order interface impact. All of the research factors significantly affected the increase in Li-Ion battery temperature, according to the hypothesis testing. |
| format | Article |
| id | doaj-art-49b830fc2c464fd296da620c3b559d94 |
| institution | OA Journals |
| issn | 2267-1242 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-49b830fc2c464fd296da620c3b559d942025-08-20T01:51:44ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016190201110.1051/e3sconf/202561902011e3sconf_icsget2025_02011Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM CompositesMarappan Muthukumar0Mahendran A.1Ravivarman G.2Suresh Kumar K.3Elango M.4Kesavan S.P.5Devarajan R.6Department of Mechanical Engineering, Nandha Engineering CollegeDepartment of Mechanical Engineering, Sona College of TechnologyDepartment of Electrical and Electronics Engineering, Karpagam Academy of Higher EducationDepartment of MBA, Panimalar Engineering CollegeDepartment of Mechanical Engineering, Erode Sengunthar Engineering CollegeDepartment of Artificial Intelligence and Data Science, Muthayammal Engineering CollegeDepartment of Electrical and Electronics Engineering, Vinayaka Mission’s Kirupananda Variyar Engineering College, Vinayaka Mission’s Research Foundation (Deemed to be University)Electric vehicles that use lithium ion (Li-Ion) batteries as an alternative to fossil fuels have emerged as a viable solution to the environmental and sustainability problems associated with these fuels. Due to their sensitivity, Li-Ion batteries have been the subject of intense heat management research for the last ten years. There are a number of ways to regulate the complicated dynamics that cause Li-Ion batteries’ temperatures to rise. This work shows how to optimize the thermal management control variables using design of experiments (DOE), keeping it as the research emphasis. The variables used for optimization include the phase change materials mass denotes as X, the thermal conduction of paraffin aluminum composite denotes as Y, and the water flow rate denotes as Z. Researchers have looked at how these factors affect the rate of heat buildup in Li-Ion batteries. Studying the effect of Li-Ion battery temperature management parameters required a full factorial DOE with two repetitions. In order to evaluate the hypotheses, multivariate analysis made use of analysis of variance (ANOVA). This included controlling for both the 1st and 2nd order interface impact. All of the research factors significantly affected the increase in Li-Ion battery temperature, according to the hypothesis testing.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_02011.pdf |
| spellingShingle | Marappan Muthukumar Mahendran A. Ravivarman G. Suresh Kumar K. Elango M. Kesavan S.P. Devarajan R. Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites E3S Web of Conferences |
| title | Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites |
| title_full | Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites |
| title_fullStr | Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites |
| title_full_unstemmed | Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites |
| title_short | Optimized Cooling Solutions for Lithium-Ion Batteries in Electric Vehicles using PCM Composites |
| title_sort | optimized cooling solutions for lithium ion batteries in electric vehicles using pcm composites |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/19/e3sconf_icsget2025_02011.pdf |
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