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EAGER: SmartGreen: An Adaptive Architecture for Management of Large Energy Storage Systems

EAGER: SmartGreen: An Adaptive Architecture for Management of Large Energy Storage Systems
EAGER:SmartGreen:大型储能系统管理的自适应架构
批准号:
1138200
负责人:
Kang Shin
金额:
$20.98万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-07-01 至 2014-06-30

项目摘要

项目成果

Kang Shin的其他基金

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中文摘要
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英文摘要
We are faced with unprecedented challenges stemming from global climate change, rising energy cost, and their impact on national competitiveness and security. To reduce greenhouse gas emissions and dependency on imported fossil fuels, it is imperative to harvest as much renewable energy as possible, which, in turn, can benefit from efficient large-scale energy storage systems that can buffer variable energy supply. Recent progress in battery technology has made it possible to use batteries to store energy, and then power platforms that incur a significant energy load, such as transportation vehicles, homes, and industrial buildings. However, the slow pace of improvement is insufficient to make the performance of rechargeable batteries competitive with, and an attractive alternative to (for example) conventional powertrains, including gasoline combustion engines. In particular, when a large number of battery cells (e.g., a 6800-cell pack for Tesla S model and a 300-cell pack for GM Volt) are put together as a pack, their electrochemical interaction and reaction can shorten the pack?s life significantly despite the high quality of individual cells. This research project explores how efficient battery management (BM) can extend the pack?s life for as long as the constituent cells can last (e.g., 10?15 years). This project is developing a holistic architecture, SMARTGREEN, based on active monitoring and control mechanisms. SMARTGREEN maximizes the synergy between battery management algorithms, software (cyber), and reconfigurable battery hardware (physical), that are tightly-coupled. SMARTGREEN focuses on: intelligent monitoring, active computation, proactive prognostics, and dynamic reconfiguration, operating in tandem to dramatically extend battery life and operation-time.
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Collaborative Research: SaTC: CORE: Medium: Securing Interactions between Driver and Vehicle Using Batteries
CPS:Small: Imposing Recovery Period for Battery Health Monitoring, Prognosis, and Optimization
CPS: Breakthrough: Secure Interactions with Internet of Things
CPS: Synergy: Adaptive Management of Large Energy Storage Systems for Vehicle Electrification