A novel approach of remaining discharge energy prediction for large format lithium-ion battery pack

2017 ◽  
Vol 343 ◽  
pp. 216-225 ◽  
Author(s):  
Xu Zhang ◽  
Yujie Wang ◽  
Chang Liu ◽  
Zonghai Chen
Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 987 ◽  
Author(s):  
Qiaohua Fang ◽  
Xuezhe Wei ◽  
Haifeng Dai

The remaining discharge energy prediction of the battery pack is an important function of a battery management system. One of the key factors contributing to the inaccuracy of battery pack remaining discharge energy prediction is the inconsistency of the state and model parameters. For a batch of lithium-ion batteries with nickel cobalt aluminum oxide cathode material, after analyzing the characteristics of battery model parameter inconsistency, a “specific and difference” model considering state of charge and R0 inconsistency is established. The dual time-scale dual extended Kalman filter algorithm is proposed to estimate the state of charge and R0 of each cell in the battery pack, and the remaining discharge energy prediction algorithm of the battery pack is established. The effectiveness of the state estimation and remaining discharge energy prediction algorithm is verified. The results show that the state of charge estimation error of each cell is less than 1%, and the remaining discharge energy prediction error of the battery pack is less than 1% over the entire discharge cycle. The main reason which causes the difference between the “specific and difference” and “mean and difference” models is the nonlinearity of the battery’s state of charge - open circuit voltage curve. When the nonlinearity is serious, the “specific and difference” model has higher precision.


2015 ◽  
Vol 154 ◽  
pp. 74-91 ◽  
Author(s):  
Xuning Feng ◽  
Xiangming He ◽  
Minggao Ouyang ◽  
Languang Lu ◽  
Peng Wu ◽  
...  

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 ◽  
...  

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