GOALI: Direct Immersion Cooling for Battery Thermal Management

GOALI：用于电池热管理的直接浸入式冷却

• 批准号: 2143043
• 负责人: Amy Marconnet
• 金额: $ 38万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143043&HistoricalAwards=false
• 关键词: GOALI; Direct; Immersion; Cooling; Battery

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.

该守门员项目的重点是直接使用液体来理解一种新方法的基本面，而不是使用液体来冷却电池，而不是传统的冷却方法，需要其他硬件来消除热量。电池电池内的温度过高和过度均匀的温度导致电池的性能和寿命降低，以及生命和财产威胁性问题，例如火灾和爆炸。通过这种新的液体冷却方法降低温度和温度的变化可以显着提高电池系统的安全性，性能和可靠性。但是冷却方法的基本面尚不清楚。需要新的冷却液来满足系统的多功能要求。需要进行模型和实验来评估新的冷却系统对电池温度的影响。该项目将通过实验和建模的组合来关注冷却流体的基本特性及其对电池本身性能的影响。这项工作中的新知识可能会改善电池，这些电池将对包括电动汽车和移动设备在内的技术的改进产生连锁反应，以及通过改善能量使用的间接在环境上间接地在环境上。这项工作集中于直接沉浸电池冷却电池，作为一种方法，作为一种方法，以减少内部温度梯度并通过三个基本的启动来改善内部温度梯度，以启用三个基本的损失：利用统计和机器学习工具来理解功能性关系关系。 （2）第二，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，以预测电池系统的性能。 （3）第三，团队将针对实验数据进行校准，然后验证建模框架，并使用它来阐明电池冷却的基本物理。该项目结合了流体分子结构和组成分析，新颖的多物理计量学和多尺理物理模型，以产生对锂离子电池细胞直接浸入冷却的基本理解所需的新知识。这项工作将结合对新冷却液的基本研究，以通过对电池耦合的热和电化学性能的实验和计算研究来增强热量耗散。最终，这项工作使改进的电池系统的合理，数据驱动的设计可以通过新的化学，材料和几何形状来确定关键性能指标的现有限制，同时保持安全性。除了该大学 - 行业伙伴关系的技术方面外，还提出了包括实习和培训计划在内的教育活动，这些活动将有助于教育下一代电池工程师和科学家。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来获得支持的。