Simulation and experimental study on lithium ion battery short circuit

Zhao, Rui; Liu, Jie; Gu, Junjie

doi:10.1016/j.apenergy.2016.04.016

Cited by 244 publications

(89 citation statements)

References 29 publications

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“…The immediate consequences of nail penetration include the occurrence of internal short circuit, which has potentially catastrophic consequences, such as fire and explosion [11][12][13]. In general, engineers must perform time-consuming and hazardous nail penetration tests [10,14]. These tests involve inserting a steel nail into LIB, thereby bridging the positive and negative electrodes within the jellyroll and causing local internal short circuit among the component interfaces of the nail and the jellyroll.…”

Section: Introductionmentioning

confidence: 99%

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Integrated computation model of lithium-ion battery subject to nail penetration

2016

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Section: Introductionmentioning

confidence: 99%

“…Recently, Chiu et al [10] modeled thermal runaway behavior during the nail penetration process. Fourth, multiphysical simulations of LIBs have been developed by researchers [14,[31][32][33]. These simulations typically involve electrochemicalthermal coupling [11,31,32] or individual jellyroll components [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Integrated computation model of lithium-ion battery subject to nail penetration

2016

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“…The , is used to estimate the initial , and the method to estimate SOC and will be explained in Section 2.3. Then the current 1 can be calculated using Equation (4) and used as input data of the RLS algorithm in Equation (5). Once the input data changes from to 1 , the estimated parameters of also change and the , can be estimated directly without the approximationassumption.…”

Section: Ocv Estimationmentioning

confidence: 99%

“…However, the Li-ion battery can develop dangerous malfunctions [2,3] such as internal short circuit (ISCr) [4,5] and cell reversal [6]; the main causes of these phenomena are overcharge [7] and overdischarge [8]. The ISCr may cause thermal runaway when the temperature rise by the ISCr in the battery exceeds a certain point [5] or the ISCr resistance R ISC f is lower than a certain value [9].…”

Section: Introductionmentioning

confidence: 99%

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

et al. 2017

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Abstract:Early detection of an internal short circuit (ISCr) in a Li-ion battery can prevent it from undergoing thermal runaway, and thereby ensure battery safety. In this paper, a model-based switching model method (SMM) is proposed to detect the ISCr in the Li-ion battery. The SMM updates the model of the Li-ion battery with ISCr to improve the accuracy of ISCr resistance R ISC f estimates. The open circuit voltage (OCV) and the state of charge (SOC) are estimated by applying the equivalent circuit model, and by using the recursive least squares algorithm and the relation between OCV and SOC. As a fault index, the R ISC f is estimated from the estimated OCVs and SOCs to detect the ISCr, and used to update the model; this process yields accurate estimates of OCV and R ISC f . Then the next R ISC f is estimated and used to update the model iteratively. Simulation data from a MATLAB/Simulink model and experimental data verify that this algorithm shows high accuracy of R ISC f estimates to detect the ISCr, thereby helping the battery management system to fulfill early detection of the ISCr.

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“…An objective function which considers the time-to-charge, energy losses and a temperature rise index is used to acquire the optimal CCCV solution. But some model parameters such as internal resistance are assumed to be constant in calculating the optimal charging current, this however will inevitably affect the efficacy of the method as variations of the battery internal resistance cannot be ignored due to its significant impact on the battery performance [23]. In addition, this strategy only considers the objective function for the CC stage in order to apply the variational method, and this inevitably affects the efficiency of the CV stage due to the fact that the current profile at the CC stage is derived separately using a different objective function.…”

Section: Introductionmentioning

confidence: 99%

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

Liu

Yang

et al. 2017

Electrochimica Acta

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. (2017) An advanced Lithiumion battery optimal charging strategy based on a coupled thermoelectric model. Electrochimica Acta, 225. pp. 330-344. Permanent WRAP URL:http://wrap.warwick.ac.uk/86302 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Kingdom (Email:{kliu02,k.li,zyang07,czhang07,j.deng}@qub.ac.uk).Abstract: Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed.Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared.The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.

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Simulation and experimental study on lithium ion battery short circuit

Cited by 244 publications

References 29 publications

Integrated computation model of lithium-ion battery subject to nail penetration

Integrated computation model of lithium-ion battery subject to nail penetration

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

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