scholarly journals Performance degradation due to anodic failure mechanisms in lithium-ion batteries

2020 ◽  
pp. 229145
Author(s):  
Abhishek Sarkar ◽  
Ikenna C. Nlebedim ◽  
Pranav Shrotriya
Keyword(s):  
Lithium Ion Batteries ◽  
Failure Mechanisms ◽  
Lithium Ion ◽  
Performance Degradation

scholarly journals Mathematical Models for the Performance Degradation of Lithium-Ion Batteries with Different Status of Charge (SOC) in Long-Term High Temperature Storage

2021 ◽  
Author(s):  
Zheng Wang ◽  
zhen Ma ◽  
Xiongfeng Hu ◽  
Ruirui Zhao ◽  
Junmin Nan
Keyword(s):  
High Temperature ◽  
Mathematical Models ◽  
Lithium Ion Batteries ◽  
Voltage Drop ◽  
Lithium Ion ◽  
Reversible Capacity ◽  
Performance Degradation ◽  
High Temperature Storage ◽  
Temperature Storage

Abstract Mathematical models to evaluate and predict the performance degradation of lithium-ion batteries (LIBs) with different status of charge (SOC) in long-term high-temperature storage which are also applicable for setting rational storage conditions (temperature, SOC, and time) of LIBs were established. Parameters including voltage drop (Delta V), reversible capacity (RC) loss, and internal impedance (IMP) increase of LIBs under different temperature (60, 45, and 25°C) are used to allow the model to clarify its function. According to the results obtained from commercial 18650 cylindrical batteries with LiNi0.33Co0.33Mn0.33O2 cathode, the mathematical relationship between Delta V and storage days (x) is fitted into a simple formula: Delta V =m.In(x)-n, and similarly, RC loss = m'.exp (n'.x) and IMP increase = m''.xn'' can also be acquired. In these formulas, m, n, m', n', m'' and n'' are constants when temperature and SOC are fixed. If only the temperature is fixed, the value of these constants can be derived into a function with SOC (y), respectively, while further plugging the function into the calculation formula of Delta V, RC loss, and IMP increase, respectively, allows the mathematical models to be set up.

scholarly journals Binder-free SnO2–TiO2 composite anode with high durability for lithium-ion batteries

RSC Advances ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 6589-6595 ◽  
Author(s):  
Hyeonseok Yoo ◽  
Gibaek Lee ◽  
Jinsub Choi
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Performance Degradation ◽  
Composite Anode ◽  
High Durability ◽  
Binder Free

A binder-free SnO2–TiO2 composite, where SnO2 is encapsulated into hollow TiO2, is designed for inhibiting performance degradation for a stable LIB anode.

scholarly journals Failure mechanisms of single-crystal silicon electrodes in lithium-ion batteries

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Feifei Shi ◽  
Zhichao Song ◽  
Philip N. Ross ◽  
Gabor A. Somorjai ◽  
Robert O. Ritchie ◽  
...  
Keyword(s):  
Single Crystal ◽  
Lithium Ion Batteries ◽  
Failure Mechanisms ◽  
Single Crystal Silicon ◽  
Lithium Ion ◽  
Crystal Silicon

Study of the Failure Mechanisms of LiNi0.8Mn0.1Co0.1O2Cathode Material for Lithium Ion Batteries

2015 ◽  
Vol 162 (7) ◽  
pp. A1401-A1408 ◽  
Author(s):  
Jing Li ◽  
Laura E. Downie ◽  
Lin Ma ◽  
Wenda Qiu ◽  
J. R. Dahn
Keyword(s):  
Lithium Ion Batteries ◽  
Failure Mechanisms ◽  
Lithium Ion

scholarly journals Constitutive Behavior and Mechanical Failure of Internal Configuration in Prismatic Lithium-Ion Batteries under Mechanical Loading

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1219
Author(s):  
Zhijie Li ◽  
Jiqing Chen ◽  
Fengchong Lan ◽  
Yigang Li
Keyword(s):  
Lithium Ion Batteries ◽  
Progressive Failure ◽  
Failure Mechanisms ◽  
Lithium Ion ◽  
Element Model ◽  
Structure Design ◽  
Mechanical Failure ◽  
Uniaxial Tensile ◽  
Failure Behavior ◽  
Short Circuits

Internal short circuits and thermal runaway in lithium-ion batteries (LIBs) are mainly caused by deformation-induced failures in their internal components. Understanding the mechanisms of mechanical failure in the internal materials is of much importance for the design of LIB pack safety. In this work, the constitutive behaviors and deformation-induced failures of these component materials were tested and simulated. The stress-strain constitutive models of the anode/cathode and the separator under uniaxial tensile and compressive loads were proposed, and maximum tensile strain failure criteria were used to simulate the failure behaviors on these materials under the biaxial indentations. In order to understand the deformation failure mechanisms of ultrathin and multilayer materials within the prismatic cell, a mesoscale layer element model (LEM) with a separator-cathode-separator-anode structure was constructed. The deformation failure of LEM under spherical punches of different sizes was analyzed in detail, and the results were experimentally verified. Furthermore, the n-layer LEM stacked structure numerical model was constructed to calculate the progressive failure mechanisms of cathodes and anodes under punches. The results of test and simulation show the fracture failure of the cathodes under local indentation will trigger the failure of adjacent layers successively, and the internal short circuits are ultimately caused by separator failure owing to fractures and slips in the electrodes. The results improve the understanding of the failure behavior of the component materials in prismatic lithium-ion batteries, and provide some safety suggestions for the battery structure design in the future.

scholarly journals Assessing the Performance Degradation of Lithium-Ion Batteries Using an Approach Based on Fusion of Multiple Feature Parameters

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Anchen Wang ◽  
Ying Zhang ◽  
Hongfu Zuo
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Degradation Process ◽  
Gaussian Mixture ◽  
Assessment Method ◽  
Performance Degradation ◽  
Discharge Voltage ◽  
Health State ◽  
Multiple Features ◽  
Feature Parameters

A method based on fusion of multiple features is proposed to assess and accurately describe the performance degradation of lithium-ion batteries in this paper. First, the discharge voltage signal of lithium-ion batteries under real-time monitoring is analyzed from the perspective of time domain and complexity to obtain the values of multiple features. Then, the multi-feature parameters undergo a spectral regression process to reduce the number of dimensions and to eliminate redundancy, and on the basis of this regression, a Gaussian mixture model is established to model the health state of batteries. Thus, the degree of lithium-ion battery performance degradation can be quantitatively assessed using the Bayesian inference-based distance metric. A case calculation experiment is carried out to verify the effectiveness of the method proposed in this paper. The experimental results demonstrate that, compared with other assessment methods, the performance degradation assessment method proposed in this paper can be used to monitor the degradation process of lithium-ion batteries more effectively and to improve the accuracy of condition monitoring of batteries, thereby providing powerful support for making maintenance decisions.

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