Pack Sizing and Reconfiguration for Management of Large-scale Batteries

被引:31
|
作者
Jin, Fangjian [1 ]
Shin, Kang G. [1 ]
机构
[1] Univ Michigan, Real Time Comp Lab, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
SWITCH ARRAY SYSTEM;
D O I
10.1109/ICCPS.2012.22
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Battery systems for electric vehicles (EVs) or uninterruptible micro-grids-prototypical cyber-physical systems (CPSs)-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.
引用
收藏
页码:138 / 147
页数:10
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