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PFI-TT: Development of a Battery Health and Safety Monitoring Technology with High Accuracy and Speed

PFI-TT: Development of a Battery Health and Safety Monitoring Technology with High Accuracy and Speed
PFI-TT:开发高精度、高速度的电池健康与安全监测技术
批准号:
2213918
负责人:
Jaber Abu Qahouq
金额:
$25.0万
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
项目状态:
未结题
起止时间:
2022-07-15 至 2025-06-30

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中文摘要
翻译
这一创新技术转化伙伴关系(PFI-TT)项目的更广泛影响/商业潜力是开发电池健康监测技术和原型系统,该系统可以比现有技术更快、更准确地检测性能恶化和可能的电池故障。快速、准确的电池健康监测影响着广泛的应用和产品,并可能对材料和人员的安全产生重大影响。电动和混合动力汽车、电动飞机、电动船只、绿色住宅和建筑、离网家庭和建筑、数据中心和计算基础设施的备用电池系统、通信系统、医院和电网或微电网规模的储能等应用和产品都是这项技术的潜在直接受益者。供电的弹性对日常生活和安全的影响越来越大。快速、准确的健康状态退化评估技术对于电池的二次利用也是非常重要的。该技术采用了新的电池健康指标、人工神经网络等先进算法,以及适合在线应用的测量方法,并以更低的成本和体积同时监控多电池组件。在这个项目中,将开发一个概念验证原型,以展示该技术的竞争优势,如精度、速度、成本和尺寸。该项目寻求使用许多参数来评估和证明该技术的商业潜力和可行性。概念验证原型还将用于向潜在的行业合作伙伴和合作伙伴展示该技术。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to develop a battery health monitoring technology and a prototype system that can detect performance deterioration and possible battery failures more quickly and accurately than current technologies. Fast and accurate health monitoring of batteries impacts a wide range of applications and products and may have significant impact on the safety of materials and personnel. Applications and products such as electric and hybrid-electric vehicles, electric aircrafts, electric boats, green homes and buildings, off-power-grid homes and buildings, backup battery systems for data centers and computing infrastructure, communication systems, hospitals and grid or micro-grid scale energy storage are potential direct beneficiaries of this technology. The resiliency of power availability increasingly impacts daily lives and security. Fast and accurate state-of-health degradation evaluation technology is also important for repurposing batteries for second-life use.The proposed project seeks to develop a battery health monitoring technology. The technology employs new battery health indicators, advanced algorithms such as Artificial Neural Networks, and measurement methods that are suitable for online applications and simultaneous multi-battery component monitoring with reduced cost and size. A proof-of-concept prototype will be developed during this project to demonstrate the competitive advantages of the technology such as accuracy, speed, cost, and size. The project seeks to evaluate and demonstrate the commercial potential and viability of the technology using many parameters. The proof-of-concept prototype will also be used to demonstrate the technology to potential industry collaborators and partners.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.
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