Dependable, efficient, scalable architecture for management of large-scale batteries

Kim, Hahnsang; Shin, Kang G.

doi:10.1145/1795194.1795219

Cited by 23 publications

(21 citation statements)

References 13 publications

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“…Then to capture the connectivity of the two terminals, we add edge n + → n i and n i → n − (i = 1, 2, · · · , N ) to E if the output terminals can be directly connected to the ith battery. Note that for many existing battery packs, the output terminals can be directed connected to any batteries through backbone buses [26]. In the following, we assume this full connectivity of the output terminals.…”

Section: B Graph Representationmentioning

confidence: 99%

“…At last, we extend the weight set W by setting w(n + ) = w(n − ) = 0. Figure 3 illustrates an example of the extended graph with N = 3 based on the battery pack design proposed in [26], as shown in Fig 3(a). With this circuit design, we can draw the current by series connecting battery-0, battery-1, and battery-2.…”

Section: B Graph Representationmentioning

confidence: 99%

“…The adaptive reconfiguration not only avoids the low efficiency issue of the traditional regulator-based approaches, but also increases the system robustness in that failed batteries can be by-passed without significantly degrading the system performance [23], [26]. Much research has been conducted to design battery systems that offer higher configuration flexibility with fewer supplementary electronic components such as connectors and switches [10], [20], [24], which has already been implemented in many off-the-shelf battery packs [8], [19], [24], [26], [39].…”

Section: Introductionmentioning

confidence: 99%

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Exploring Adaptive Reconfiguration to Optimize Energy Efficiency in Large-Scale Battery Systems

Kong

et al. 2013

2013 IEEE 34th Real-Time Systems Symposium

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Abstract-Large-scale battery packs with hundreds/thousands of battery cells are commonly adopted in many emerging cyberphysical systems such as electric vehicles and smart micro-grids. For many applications, the load requirements on the battery systems are dynamic and could significantly change over time. How to resolve the discrepancies between the output power supplied by the battery system and the input power required by the loads is key to the development of large-scale battery systems. Traditionally, voltage regulators are often adopted to convert the voltage outputs to match loads' required input power. Unfortunately, the efficiency of utilizing such voltage regulators degrades significantly when the difference between supplied and required voltages becomes large or the load becomes light. In this paper, we propose to address this problem via an adaptive reconfiguration framework for the battery system. By abstracting the battery system into a graph representation, we develop two adaptive reconfiguration algorithms to identify the desired system configurations dynamically in accordance with real-time load requirements. We extensively evaluate our design with empirical experiments on a prototype battery system, electric vehicle driving trace-based emulation, and battery discharge trace-based simulations. The evaluation results demonstrate that, depending on the system states, our proposed adaptive reconfiguration algorithms are able to achieve 1× to 5× performance improvement with regard to the system operation time.

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Section: B Graph Representationmentioning

confidence: 99%

Section: B Graph Representationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploring Adaptive Reconfiguration to Optimize Energy Efficiency in Large-Scale Battery Systems

Kong

et al. 2013

2013 IEEE 34th Real-Time Systems Symposium

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“…With the switches in packs, we can organize cells in series, parallel or many parallel branches of series. The design details of switches, controllers and sensors of SoC can be found in [10], [11]. We can treat a battery pack as a module, just like a single cell, and to use switches around packs to reconfigure them.…”

Section: A Reconfigurable Battery Systemmentioning

confidence: 99%

Pack Sizing and Reconfiguration for Management of Large-Scale Batteries

Jin

Shin

2012

2012 IEEE/ACM Third International Conference on Cyber-Physical Systems

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Abstract-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 largescale 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.

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“…The performance of unbalanced battery system is fundamentally limited by the weakest cell, to avoid issues such as thermal runaway [7], [8]. This is particular critical for cells connected in series, because the strength of a cell string is only as strong as the weakest cell.…”

mentioning

confidence: 99%

RAC: Reconfiguration-Assisted Charging in Large-Scale Lithium-Ion Battery Systems

Kong

Lin

et al. 2016

IEEE Trans. Smart Grid

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Large-scale lithium-ion battery packs are widely adopted in systems such as electric vehicles and energy backup in power grids. Due to factors such as manufacturing difference and heterogeneous discharging conditions, cells in the battery pack may have different statuses, such as diverse voltage levels. This cell diversity is commonly known as the cell imbalance issue. For the charging of battery packs, the cell imbalance not only early on terminates the charging process before all cells are fully charged, but also leads to different desired charging currents among cells. In this paper, based on the advancement in reconfigurable battery systems, we demonstrate how to utilize system reconfigurability to mitigate the impact of cell imbalance on an efficient charging process. With the proposed reconfigurationassisted charging (RAC), cells in the system are categorized according to their real-time voltages, and the charging process is performed in a category-by-category manner. To charge cells in a given category, a graph-based algorithm is presented to charge cells with their desired charging currents, respectively. We evaluate RAC through both experiments and simulations. The results demonstrate that the RAC increases the capacity charged into cells by about 25% and yields a dramatically reduced variance.

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Dependable, efficient, scalable architecture for management of large-scale batteries

Cited by 23 publications

References 13 publications

Exploring Adaptive Reconfiguration to Optimize Energy Efficiency in Large-Scale Battery Systems

Exploring Adaptive Reconfiguration to Optimize Energy Efficiency in Large-Scale Battery Systems

Pack Sizing and Reconfiguration for Management of Large-Scale Batteries

RAC: Reconfiguration-Assisted Charging in Large-Scale Lithium-Ion Battery Systems

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