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June 2, 2017

Electronic circuit boards (Image 3)

Electronic circuit boards for dependable, efficient, scalable architecture for large-scale battery management. [Image 3 of 3 related images. Back to Image 1.]

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In order to reduce greenhouse gas emissions and the nation's dependency on imported fossil fuels, it is vital that we 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.

Kang G. Shin, the Kevin and Nancy O'Connor Professor of Computer Science and the founding director of the Real-Time Computing Laboratory (RTCL) in the Electrical Engineering and Computer Science Department at the University of Michigan, received a grant from the National Science Foundation (CNS 11-38200) to explore how efficient battery management can extend a pack's life for as long as the constituent cells can last (e.g., 10 or 15 years). The project is developing a holistic architecture, called 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.

Further information about this research is available on the RTCL website Here. (Date of Image: May 2012)

Credit: Computer Science and Engineering Division of the Electrical Engineering and Computer Science Department, University of Michigan

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