Optimal Thermal Management of Electric Vehicle Battery Systems Using Serpentine Minichannel Cold Plates with Intersecting V-Shaped Minichannels
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| details: | Mahmood, Ahmed, de Boer, Gregory, Cockerill, Timothy, Raihan, Muhammad F. B., Thompson, Harvey and Voss, Jochen: Optimal Thermal Management of Electric Vehicle Battery Systems Using Serpentine Minichannel Cold Plates with Intersecting V-Shaped Minichannels. Journal of Energy Storage, pp. 118995, 2025. |
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| online: | DOI:10.1016/j.est.2025.118995 |
| metadata: | BibTeX, Google |
| keywords: | Li-ion batteries, electric vehicles, thermal management, computational fluid dynamics, machine learning, multi-objective design optimization |
Abstract
Environmental concerns are promoting the shift towards electric vehicles (EVs) from internal combustion-based vehicles. Lithium ion (Li-ion) batteries are currently the dominant power source option for modern electric vehicles (EVs); however, their operating temperatures need to remain within an allowable safety range in order to preserve battery lifetime and avoid thermal runaway. Accordingly, high-performance battery thermal management systems (BTMSs) are needed for safe and efficient battery operation. These challenges are addressed here using a novel machine learning (ML)-enabled multi-objective optimization (MOO) approach for BTMS based on serpentine minichannel cold plates with intersecting V-shaped minichannels (SMCCP-IVSMC).
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