SBIR Phase I: Impedance-Based Battery Health Management for Large Format Lithium-Ion Battery Packs

SBIR 第一阶段：针对大型锂离子电池组的基于阻抗的电池健康管理

• 批准号: 1842957
• 负责人: Steven Chung
• 金额: $ 22.5万
• 依托单位: Rejoule Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842957&HistoricalAwards=false
• 关键词: SBIR; Phase; Impedance; Based; Battery

The broader impact/commercial potential of this project is the advancement of battery technologies. The race for the perfect battery is intensifying due to growing global demand for both the electric vehicle (EV) and stationary storage industries. The search is on for new ways to improve energy and power density, reduce charging time, and extend battery life. The project will create a diagnostic tool that provides an unprecedented glimpse inside the battery and has the potential to accelerate scientific understanding of how batteries age. A more accurate assessment of battery degradation in real time can inform on-board algorithms, can improve overall battery pack efficiency, and has major cost saving impacts for automakers and stationary storage users. This predictability enables more cost-effective warranty management, improved charging and safety algorithms, and ever more efficient battery pack designs. Having a sense of remaining useful life also enables the battery to be re-used in a secondary application - creating new business opportunities while a new revenue stream making batteries more sustainable. Ultimately, this reduces costs for both consumers and manufacturers, and contributes to greener use of resources for society. This Small Business Innovation Research (SBIR) Phase I project unlocks key insights for large-format lithium batteries. Today?s battery management systems (BMS) do not track a battery?s actual degradation metrics so it cannot forecast remaining useful life. This makes it hard to predict the ?cliff?, a sudden and steep drop in capacity near a battery?s end of life. This forces battery makers to overdesign battery systems to reduce chances of premature failure before the warranty expiration. The proposed research employs electrochemical impedance spectroscopy (EIS) onboard a BMS. EIS is a diagnostic tool that measures battery impedance - something only possible in a lab setting today. Tracking impedance unlocks a lifetime of degradation data and helps battery engineers better understand the long-term degradation behavior of high voltage battery packs. The project will focus on 1) minimizing the required hardware to measure impedance of each cell in a series-connected battery pack, and 2) reducing the down-time associated with the impedance measurement. The proposed innovation blends a unique hardware architecture with wide-bandgap semiconductors and adaptive charge-control algorithms to minimize hardware size. These help to reduce overall system cost and unlocks orders of magnitude improvement in hardware scalability over existing EIS methods.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.

该项目的更广泛的影响/商业潜力是电池技术的进步。由于全球对电动汽车（EV）和固定储存行业的需求不断增长，因此完美电池的比赛正在加剧。搜索正在寻找改善能源和功率密度，减少充电时间并延长电池寿命的新方法。该项目将创建一种诊断工具，该工具在电池内提供了前所未有的瞥见，并有可能加速科学了解电池的年龄。实时对电池降解的更准确评估可以告知车载算法，可以提高整体电池组效率，并对汽车制造商和固定存储用户产生重大的成本节省影响。这种可预测性可实现更具成本效益的保修管理，改进的充电和安全算法以及更有效的电池组设计。 具有剩余的使用寿命的感觉也使电池能够在次要应用中重新使用 - 创造新的商机，而新的收入流使电池更具可持续性。 最终，这降低了消费者和制造商的成本，并有助于更绿色地使用资源为社会使用。这项小型企业创新研究（SBIR）I期项目解锁了大型锂电池的关键见解。如今，电池管理系统（BMS）不跟踪电池的实际降解指标，因此无法预测剩余的使用寿命。这使得很难预测悬崖？，在电池末端的生命尽头的容量突然下降。 这迫使电池制造商过度设计电池系统，以减少保修到期之前过早故障的机会。拟议的研究采用ABMS的电化学阻抗光谱（EIS）。 EIS是一种测量电池阻抗的诊断工具 - 当今只有在实验室设置中才有可能。跟踪阻抗可以解锁终生降解数据，并帮助电池工程师更好地了解高压电池组的长期退化行为。该项目将集中在1）最小化所需的硬件以测量连接电池组中每个单元的阻抗，以及2）减少与阻抗测量相关的停机时间。提出的创新将独特的硬件体系结构与宽带的半导体和自适应电荷控制算法融合在一起，以最大程度地减少硬件尺寸。这些有助于降低整体系统成本，并解锁硬件可伸缩性比现有EIS方法的数量级提高。该奖项反映了NSF的法定任务，并且使用基金会的智力优点和更广泛的审查标准，被认为值得通过评估来获得支持。