Numerical simulation model for short circuit prediction under compression and bending of 18650 cylindrical lithium-ion battery

Sheikh, Muhammad Aman; Rehman, Sheikh; Elkady, Mustafa

doi:10.1016/j.egypro.2018.09.046

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…For the rigid base plate, MAT_20_RIGID is used to turn the solid element part into a rigid body. Detailed properties and relevant characteristics of materials used can be found in LS-DYNA material model manual [45]. Element size selection is crucial which affects computation efficiency as well as stability of the model.…”

Section: Validation Of Experimental Resultsmentioning

confidence: 99%

“…Element size selection is crucial which affects computation efficiency as well as stability of the model. Material properties for current collectors and active materials are used from [45][46][47][48][49] and experimental study, which are given in table 3.…”

Section: Validation Of Experimental Resultsmentioning

confidence: 99%

“…Detailed properties and relevant characteristics of materials used can be found in the LS-DYNA material model manual. 45 Element size selection is crucial which affects computation efficiency as well as stability of the model. Material properties for current collectors and active materials are used from Refs.…”

Section: Validation Of Experimental Resultsmentioning

confidence: 99%

“…In [21][22][23] various loading conditions are discussed, however a full understanding of loading-dependent and electrochemical-dependent mechanical behaviours of lithiumion battery components is essential for battery safety, optimization and evaluation [24].…”

Section: Journal Of the Electrochemical Societymentioning

confidence: 99%

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Internal Short Circuit Analysis of Cylindrical Lithium-Ion Cells Due to Structural Failure

Sheikh

Elmarakbi²,

Rehman

et al. 2021

J. Electrochem. Soc.

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Battery failures are obvious after being subject to abuse conditions however predicting these failures in advance is crucial when using test and validation techniques to understand battery potential. Lithium-ion battery cells are widely used due to their high energy and power densities. When abusive conditions like the three point bend loading are applied to lithium-ion batteries, what occurs to the mechanical behaviours and components is still mostly unknown. To further this understanding, this paper investigates the mechanical behaviour of the separator in the LiCoO2/Graphite cylindrical 18650 cells. Internal short circuit (ISC) behaviour, strain rate dependency and electrochemical status of the cells (i.e. SOC dependency) are studied to understand failure pattern. Furthermore, simple and effective constitutive model for the separator layer is formed, facilitating further mechanical analysis and numerical simulation of lithium-ion battery study. Occurrence of ISC is investigated by jellyroll deformation where casing is removed, and quasi-static load is applied. Numerical simulation model is developed to further investigate sequential structural failures and temperature changes. Simulation results showed good accuracy with experimental results and are useful to predict structural failure of cells. Number of failures including electrolyte leakage, change in shape, sudden voltage drop/temperature rise, and gas venting are observed.

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Section: Validation Of Experimental Resultsmentioning

confidence: 99%

Section: Validation Of Experimental Resultsmentioning

confidence: 99%

Section: Validation Of Experimental Resultsmentioning

confidence: 99%

Section: Journal Of the Electrochemical Societymentioning

confidence: 99%

See 2 more Smart Citations

Internal Short Circuit Analysis of Cylindrical Lithium-Ion Cells Due to Structural Failure

Sheikh

Elmarakbi²,

Rehman

et al. 2021

J. Electrochem. Soc.

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Artificial Neural Network–Based Multisensor Monitoring System for Collision Damage Assessment of Lithium‐Ion Battery Cells

Zhang

Simeone

2020

Energy Tech

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The sales of electric vehicles (EVs) have seen a significant upward trend in recent years. The occurrence of severe collision accidents has raised awareness concerning safety issues of lithium‐ion batteries (LIBs) which are the core components of EV energy storage systems. When collision accidents of vehicles occur, in most cases, the battery cells will immediately burn and even explode, whereas in some cases, despite not directly showing visual damages, the battery cells may lead to delayed catastrophic failures. Herein, the assessment of the battery cells collision damage based on sensor signal data is focused on by identifying potentially unsafe cells. A campaign of collision experimental tests and a series of electrical performance tests are conducted on single‐cell specimens. A cell damage characterization procedure is proposed and implemented on the battery cells after the collision tests. The impact force and z‐axis acceleration signal features and respective damage classes are input to an artificial neural network (ANN) pattern classifier to train a model to assess the battery cell collision damage.

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Characterization of external short circuit faults in electric vehicle Li-ion battery packs and prediction using artificial neural networks

et al. 2020

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Numerical simulation model for short circuit prediction under compression and bending of 18650 cylindrical lithium-ion battery

Cited by 10 publications

References 28 publications

Internal Short Circuit Analysis of Cylindrical Lithium-Ion Cells Due to Structural Failure

Internal Short Circuit Analysis of Cylindrical Lithium-Ion Cells Due to Structural Failure

Artificial Neural Network–Based Multisensor Monitoring System for Collision Damage Assessment of Lithium‐Ion Battery Cells

Characterization of external short circuit faults in electric vehicle Li-ion battery packs and prediction using artificial neural networks

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