A Distributed Industrial Battery Management Network

Lim, D.; Anbuky, A.H.

doi:10.1109/tie.2004.837870

Cited by 23 publications

(12 citation statements)

References 12 publications

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“…With the wide adoption of battery systems such as electric vehicles and aircraft [2,6,30,39], significant research effort has been devoted to improving the system performance through effective system monitoring [25], advanced design of battery management systems [13,21,31,35,36], optimal battery discharge scheduling [11,12,14,23,33,42], etc.…”

Section: Related Workmentioning

confidence: 99%

Gü

Zhu

et al. 2015

Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems

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Unbalanced battery cells are known to significantly degrade the performance and reliability of a large-scale battery system. In this paper, we exploit emerging reconfigurable battery packs to mitigate the cell imbalance via the joint consideration of system reconfigurability and State-of-Health (So-H) of cells. Via empirical measurements and validation, we observe that a significantly larger amount of capacity can be delivered when cells with similar SoH levels are connected in series during discharging, which in turn extends the system operation time. Based on this observation, we propose two SoH-aware reconfiguration algorithms focusing on fully and partially reconfigurable battery packs, and prove their (near) optimality. We evaluate the proposed SoH-aware reconfiguration algorithms using both experiments and simulations. The algorithms are shown to deliver about 10-30% more capacity than SoH-oblivious configuration approaches.

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Section: Related Workmentioning

confidence: 99%

Gü

Zhu

et al. 2015

Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems

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“…This is because when the required voltage increases, the load current decreases with a fixed required power, which in turn leads to a longer operation time. However, as the required voltage continuously increases (e.g., [25,30]), the probability for the fixed configuration to not able to support such required voltage increases, and thus the operation time is reduced.…”

Section: Battery Voltage Diversitiesmentioning

confidence: 99%

“…RELATED WORK Large-scale battery systems are commonly adopted in practice, and many research efforts have been devoted to improve the system performance focusing on the battery discharge scheduling [11], [14], [17], [25], [32], the effective system monitoring [27], the design of battery management systems [16], [30], [38], etc.…”

Section: B Emulation Based On Electric Vehicle Driving Tracesmentioning

confidence: 99%

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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“…The controller area network has been employed in many domains [1]- [8] during the past years due to its advantages, for instance, automobile, security and the other industry control. In particular, its application fields are still significantly increasing.…”

Section: Introductionmentioning

confidence: 99%

Online Fault Diagnosis for Controller Area Networks

Qin

2011

2011 Fourth International Conference on Intelligent Computation Technology and Automation

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The controller area network (CAN) is a field bus that has been widely used in distributed embedded systems due to its inexpensiveness, robustness, guarantee of latency times as well as error detection. However, electromagnetic interference from the operational environment and hardware malfunction may cause short disturbances and permanent failures respectively, inevitably bring on communication errors or even break off the communication. To enhance the dependability of CAN communication, research on the on-line fault diagnosis is carried out in this paper, a Monitor is designed to diagnose faults in CAN nodes and a hybrid method with active and passive mode is presented to diagnose faults among communication links. We analyze the relative works, describe the CAN fault model, and focus on the fault diagnosis mechanisms.

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A Distributed Industrial Battery Management Network

Cited by 23 publications

References 12 publications

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

Online Fault Diagnosis for Controller Area Networks

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