Voltage fault detection for lithium-ion battery pack using local outlier factor

Measurement ◽  
2019 ◽  
Vol 146 ◽  
pp. 544-556 ◽  
Author(s):  
Zonghai Chen ◽  
Ke Xu ◽  
Jingwen Wei ◽  
Guangzhong Dong
2015 ◽  
Vol 48 (21) ◽  
pp. 1465-1470 ◽  
Author(s):  
Zhentong Liu ◽  
Hongwen He ◽  
Qadeer Ahmed ◽  
Giorgio Rizzoni

Author(s):  
Michael J. Rothenberger ◽  
Jariullah Safi ◽  
Ji Liu ◽  
Joel Anstrom ◽  
Sean Brennan ◽  
...  

This article optimizes the allocation of external current demand among parallel strings of cells in a lithium-ion battery pack to improve Fisher identifiability for these strings. The article is motivated by the fact that better battery parameter identifiability can enable the more accurate detection of unhealthy outlier cells. This is critical for pack diagnostics. The literature shows that it is possible to optimize the cycling of a single battery cell for identifiability, thereby improving the speed and accuracy with which its health-related parameters can be estimated. However, the applicability of this idea to online pack management is limited by the fact that overall pack current is typically dictated by the user, and difficult to optimize. We circumvent this challenge by optimizing the internal allocation of total pack current for identifiability. We perform this optimization for two pack designs: one that exploits switching control to allocate current passively among parallel strings of cells, and one that incorporates bidirectional DC–DC conversion for active charge shuttling among the strings. A novel evolutionary algorithm optimizes identifiability for each pack design, and a local outlier probability (LoOP) algorithm is then used for diagnostics. Simulation studies show significant improvements in diagnostic accuracy for an automotive protocol.


Author(s):  
Xia Hua ◽  
Alan Thomas

Lithium-ion batteries are being increasingly used as the main energy storage devices in modern mobile applications, including modern spacecrafts, satellites, and electric vehicles, in which consistent and severe vibrations exist. As the lithium-ion battery market share grows, so must our understanding of the effect of mechanical vibrations and shocks on the electrical performance and mechanical properties of such batteries. Only a few recent studies investigated the effect of vibrations on the degradation and fatigue of battery cell materials as well as the effect of vibrations on the battery pack structure. This review focused on the recent progress in determining the effect of dynamic loads and vibrations on lithium-ion batteries to advance the understanding of lithium-ion battery systems. Theoretical, computational, and experimental studies conducted in both academia and industry in the past few years are reviewed herein. Although the effect of dynamic loads and random vibrations on the mechanical behavior of battery pack structures has been investigated and the correlation between vibration and the battery cell electrical performance has been determined to support the development of more robust electrical systems, it is still necessary to clarify the mechanical degradation mechanisms that affect the electrical performance and safety of battery cells.


Author(s):  
Yabo Wang ◽  
Zhao Rao ◽  
Shengchun Liu ◽  
Xueqiang Li ◽  
Hailong Li ◽  
...  

Author(s):  
Chalukya Bhat ◽  
Janamejaya Channegowda ◽  
Victor George ◽  
Shilpa Chaudhari ◽  
Kali Naraharisetti

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