NDLI: Pack Sizing and Reconfiguration for Management of Large-Scale Batteries

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Pack Sizing and Reconfiguration for Management of Large-Scale Batteries

Content Provider	ACM Digital Library
Author	Jin, Fangjian Shin, Kang G.
Abstract	Battery systems for electric vehicles (EVs) or uninterruptible micro-gridsâ "prototypical cyber-physical systems (CPSs)â "are usually built with several hundreds/thousands of battery cells. How to deal with the inevitable failure of cells quickly and cost-effectively for vehicle warranty or uninterruptible service, for instance, is key to the development of large-scale battery systems. Use of extra (redundant/backup) cells to cope with cell failures must be minimized so as to make the target systems cheaper and lighter, while meeting the reliability requirement that is directly related to, for example, the vehicle warranty. Existing reconfigurable battery systems do not scale well because they incur a long delay in properly setting a large number of switches to bypass faulty cells or adapting to dynamically changing power demands in large battery systems for such applications as EVs. In this paper, we propose a scalable solution, not only to reduce the required number of backup cells and the total cost of a battery system, but also to facilitate recovery from cell failures and adapt to changing power demands while increasing battery utilization. Specifically, we optimize the pack-size by striking a balance between various types of cost in order to reduce the overall cost. We also configure battery packs and optimize their connection topology, reducing delays in failure recovery and power reallocation. Our in-depth evaluation has shown that the time to recover from cell failures remains constant irrespective of the number of cells involved, which is important to scalability. The proposed pack-sizing also reduces the cost and the size of battery systems. Moreover, fast power reallocation is achieved by utilizing prior knowledge of power usage patterns.
Starting Page	138
Ending Page	147
Page Count	10
File Format	PDF
ISBN	9780769546957
DOI	10.1109/ICCPS.2012.22
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-04-17
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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