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Battery space optimization to limit heat transfer in a lithium-ion battery using adaptive elephant herding optimization

机译:电池空间优化,利用自适应大象挤出优化限制锂离子电池的热传递

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摘要

Pure electric vehicles have a variety of benefits such as energy efficiency, zero environmental emissions, elimination in air pollution, and decreased carbon dioxide emissions. While it offers major benefits, it suffers from numerous battery-related issues, and, among them, heat dissipation is considered to be a major challenge, leading to significant performance degradation if not handled properly. In this present work, a battery thermal management system design is presented using ANSYS Fluent and adaptive elephant herding optimization algorithm for optimizing the battery spacing, reducing the heat dissipation, and ensuring a proper battery temperature in the lithium-ion battery pack. The adaptive elephant herding optimization algorithm provides an optimal battery spacing of (17, 23, 21, 0.23, 0.23, 0.174, 0.174), and the maximum temperature, minimum temperature, and temperature difference values observed are 298.3112 K, 292.9874 K, and 5.47 K, respectively. The research findings show that the adaptive elephant herding optimization algorithm works as an appropriate cost-effective strategy for depicting the influence of the battery spacing towards the battery temperature and results in a uniform cooling of the entire battery pack.
机译:纯电动车具有各种益处,如能量效率,零环境排放,空气污染消除,减少二氧化碳排放。虽然它提供了重大好处,但它受到众多与电池相关的问题,而且,其中,散热被认为是一个重大挑战,导致如果没有正确处理,导致显着的性能下降。在本工作中,使用ANSYS流畅和自适应的大象放牧优化算法来提供电池热管理系统设计,用于优化电池间距,降低散热,并确保锂离子电池组中的适当电池温度。自适应大象封装优化算法提供了(17,23,21,203,0.23,20.12,0.174)的最佳电池间隔,以及观察到的最高温度,最小温度和温度差值是298.3112 k,292.9874k和5.47 k分别。研究结果表明,自适应大象放牧优化算法作为一种适当的经济有效策略,用于描绘电池间距对电池温度的影响,并导致整个电池组的均匀冷却。

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