GOALI: Direct Immersion Cooling for Battery Thermal Management

这个GOALI项目的重点是了解一种直接用液体冷却电池的新方法的基本原理，而不是需要额外硬件来去除热量的传统冷却方法。电池单元内过高和不均匀的温度会导致电池的性能和寿命降低，以及威胁生命和财产的问题，如火灾和爆炸。通过这种新的液体冷却方法降低温度和温度变化可以显着提高电池系统的安全性，性能和可靠性。但冷却方法的基本原理还没有得到很好的理解。需要新的冷却液来满足系统的多功能要求。需要模型和实验来评估新冷却系统对电池温度的影响。该项目将通过实验和建模相结合，重点研究冷却液的基本特性及其对电池本身性能的影响。这项工作的新知识可以导致电池的改进，这将对电动汽车和移动的设备等技术的改进产生涟漪反应，并通过改善能源使用间接影响环境。这项工作的重点是电池单元的直接浸入式冷却，作为一种减少内部温度梯度并通过三个基本目标提高性能的方法：（1）首先，该团队将通过实验评估配方对新型浸没式冷却液的影响，然后利用统计和机器学习工具来了解功能-属性关系。(2)其次，将建立一个数据驱动的建模框架，以整合有关热、电化学和流体传输特性的实验数据，从而预测电池系统的性能。(3)第三，该团队将根据实验数据校准，然后验证建模框架，并使用它来阐明电池冷却的基本物理学。该项目结合了流体分子结构和成分分析，新颖的多物理计量学和多尺度物理建模，以产生对锂离子电池直接浸没冷却的基本理解所必需的新知识。这项工作将结合联合收割机的基础研究，新的冷却液，以提高散热的实验和计算研究的耦合热和电化学性能的电池。最终，这项工作可以实现改进电池系统的合理，数据驱动的设计，通过新的化学，材料和几何形状，推动关键性能指标的现有限制，同时保持安全性。除了技术方面的大学和产业合作，还提出了包括实习和培训计划在内的教育活动，以促进下一代电池工程师和科学家的教育。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This GOALI project focuses on understanding the fundamentals of a new approach to cool battery cells directly with a liquid instead of conventional cooling method requiring additional hardware for removing the heat. Excessive and non-uniform temperatures within battery cells lead to reduced performance and lifetime of the batteries, as well as life- and property-threatening issues such as fires and explosions. Reducing the temperatures and variations in temperature through this new liquid cooling approach could significantly enhance the safety, performance, and reliability of the battery systems. But the fundamentals of the cooling approach are not well understood. New cooling fluids are needed to meet the multi-functional requirements of the system. Models and experiments are needed to assess the impact of the new cooling system on the battery temperatures. This project will focus on both the fundamental properties of the cooling fluid and its impact on the performance of the battery itself through a combination of experiments and modeling. New knowledge from this work can lead to improvements to batteries that will have a ripple effect on improvements to technology including electric vehicles and mobile devices, as well as indirectly on the environment through improved energy usage.This work focuses on direct immersion cooling of battery cells as a method to reduce internal temperature gradients and improve performance through three fundamental thrusts: (1) First, the team will experimentally evaluate the impact formulations have on new immersion cooling fluids then leverage statistical and machine learning tools to understand the function-property relations. (2) Second, a data-driven modeling framework will be established to integrate experimental data on thermal, electrochemical, and fluid transport properties to predict performance of the battery system. (3) Third, the team will calibrate, then validate, the modeling framework against experimental data and use it to elucidate the fundamental physics of battery cooling. This project combines fluid molecular structure and composition analysis, novel multi-physics metrology, and multiscale physics modeling to generate the new knowledge necessary for a fundamental understanding of direct immersion cooling of lithium-ion battery cells. This work will combine fundamental studies of new cooling fluids to enhance heat dissipation with experimental and computational investigation of the coupled thermal and electrochemical performance of battery cells. Ultimately, this work enables the rational, data-driven design of improved battery systems that push the existing limits on key performance metrics, while maintaining safety, through new chemistries, materials, and geometries. Beyond the technical aspects of this university-industry partnership, educational activities including internships and training programs are proposed that would facilitate educating the next generation of battery engineers and scientists.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.