| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | June 28, 2011 |
| Latest Amendment Date: | June 28, 2011 |
| Award Number: | 1138200 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Marilyn McClure
mmcclure@nsf.gov (703)292-5197 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | July 1, 2011 |
| End Date: | June 30, 2014 (Estimated) |
| Total Intended Award Amount: | $209,823.00 |
| Total Awarded Amount to Date: | $209,823.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1109 GEDDES AVE STE 3300 ANN ARBOR MI US 48109-1015 (734)763-6438 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
MI US 48109-1274 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CSR-Computer Systems Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project has made a significant scientific advance in realizing energy-efficient and environment-friendly battery-powered platforms, such as transportation vehicles and buildings by rigorously and systematically addressing the problems associated with battery-cell failures and decrease in actual capacity of battery packs, each built with hundreds of cells. The solutions developed extends significantly the operation-time and lifetime of large-scale battery packs even in the presence of random battery-cell failures.The battery packs are discharged at as constant a rate as possible irrespective of fluctuating loads, thus extending their lifetime. It also tolerates inevitable battery-cell failures in large battery packs by automatically detecting and bypassing the faulty cells in real time.
This project has made several broader implications. First, its results will make significant economical and environmental impacts by solving a key problem of green platforms--battery management--which will, in turn, make the platforms more reliable, cheaper, and hence more affordable. The resulting increase in platform (e.g., vehicles) owner/user population will reduce fuel consumption and hence, emission of CO2. Second, this project has introduced an interesting new CPS research area that we call cyber-physical-physical-systems where ``battery-platform'' is an example of ``physical-physical.''Third, it will stimulate many team efforts that combine a diverse set of disciplines, such as computer HW and SW, electrical engineering,chemical engineering, material science, mechanical and industrial engineering, and even economics and businesses. Finally, the developed solutions have been transitioned to industry by their licensing to energy storage systems companies.
Last Modified: 01/01/2015
Modified by: Kang G Shin
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