利用复合相变材料进行电池热管理的最新进展

Energy Storage Pub Date : 2024-06-01 DOI:10.1002/est2.647
SR Shravan Kumar, G. Amba Prasad Rao
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引用次数: 0

摘要

电动汽车可使交通领域脱碳,并有效实现可持续发展目标。一个良好的电池热管理系统(BTMS)对装有锂离子电池(LIB)的电动汽车的安全工作至关重要,可有效解决热失控和相关的灾难性危险。然而,PCM 存在热传导率低的问题,因此,增强技术包括使用鳍片、纳米添加剂、扩展石墨粉等。使用复合相变材料可有效解决电动汽车中广泛使用的 LIB 热管理问题,同时缓解热失控,此外还具有阻燃、热/机械稳定性、电绝缘和防止泄漏的作用。我们注意到,没有一种单一的 BTMS 策略能将温度降至安全区域,目前采用的混合 BTMS 在很大程度上都涉及相变材料 (PCM)。考虑到车辆的驾驶周期和运行条件,利用 CPCM 解决低温环境和振动的影响至关重要。从综述中可以看出,超声波监测和内部短路的早期检测是缓解热失控传播的步骤。需要利用优化方法、机器学习和物联网工具来实现可行的基于 PCM 的 BTMS 工作。本综述简要介绍了有效利用 PCM 的潜在方法、不同方法之间的比较、相关挑战和潜在解决方案。为使 LIB 运行得更好、更安全,开发配备有效 CPCM 的紧凑型、经济型 BTMS 至关重要,这样才能吸引电动汽车的大规模商业化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent progress on battery thermal management with composite phase change materials

Electric mobility decarbonizes the transportation sector and effectively addresses sustainable development goals. A good battery thermal management system (BTMS) is essential for the safe working of electric vehicles with lithium-ion batteries (LIBs) to address thermal runaway and associated catastrophic hazards effectively. However, PCMs suffer from low thermal conductivity issues, and hence, enhancement techniques include the use of fins, nano-additives, extended graphite powder, and so forth. The use of composite phase change materials effectively addresses LIB thermal management widely used in electric vehicles while mitigating thermal runaway, besides providing flame retardancy, thermal/mechanical stability, and electrical insulation, and preventing leakage. It is noted that no single strategy of BTMS is brought down to a safe zone of temperature, and hybrid BTMSs are being employed, invariably involve phase change materials (PCMs) to a large extent. It is essential to utilize CPCMs to address the effects of low-temperature environments and vibrations considering vehicle driving cycles and operating conditions. It is observed from the review that ultrasonic monitoring and early detection of internal short circuits are the steps towards mitigation of thermal runaway propagation. It is required to utilize optimization methods, machine learning and IoT tools for a feasible PCM based BTMS work. Present review briefly describes potential methods for effective utilization of PCMs, comparison among different methods, challenges associated and potential solutions. It is highly essential to develop compact and economical BTMS with effective CPCMs for better and safer LIB operation to attract large-scale commercialization of electric vehicles.

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