Predicting short circuit of Li-ion battery cells during mechanical abuse

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dc.contributor.authorPurantagi, Ankeet Mohan
dc.contributor.departmentChalmers tekniska högskola / Institutionen för industri- och materialvetenskapsv
dc.contributor.departmentChalmers University of Technology / Department of Industrial and Materials Scienceen
dc.contributor.examinerLarsson, Fredrik
dc.contributor.supervisorVikström, Simon
dc.contributor.supervisorCarlstedt, David Carlstedt
dc.contributor.supervisorGustavsson, Peter
dc.date.accessioned2024-09-20T10:14:38Z
dc.date.available2024-09-20T10:14:38Z
dc.date.issued2024
dc.date.submitted
dc.description.abstractithium-ion (Li-ion) batteries are today’s preferred energy storage solution for electric vehicles (EVs). Ensuring safety in their design is crucial, especially in car accidents, where mechanical damage to battery cells can cause internal electric short circuits, posing significant risks. Thus, minimising the occurrence of such incidents is paramount. The growing adoption of EVs also heightens the risk of thermal runaway following crashes, whether from side, frontal, rear, or bottom impacts. This concern underscores the necessity of developing virtual testing models to mitigate the costs of real-life battery crash testing. This thesis aimed to develop a finite element (FE) modelling methodology to predict internal short circuits in Li-ion batteries. The test data used in this work was obtained from previous tests, serving as the reference material behaviour response curve (force vs. displacement) upon which the subsequent research was based. The study was conducted in two different loading directions. Four test cases (two for each loading direction) were considered to create a homogenised material model. Multiple parametric optimisation runs were performed better to fit the material model’s response to the test. The final optimisation run achieved a realistic material behaviour that closely matched the test data. This single homogenised material model was then used to predict the short-circuit behaviour of the Li-ion battery in the specified scenarios. The conclusions drawn from this thesis validate the assumption that the material behaves anisotropically, with the global response closely matching the test data. While the failure models used in these cases may apply to certain scenarios, there is a need for more test data to understand the material behaviour and its response better. This additional data will aid in developing the failure surface of the battery material. Given the complexity of battery material behaviour, future work should consider various other factors, such as internal pressure build-up, swelling effects, state of charge (SoC) and internal loads like buckling by increasing the number of resolved layers. These factors significantly influence the material response and should be explored further.
dc.identifier.coursecodeIMSX30
dc.identifier.urihttp://hdl.handle.net/20.500.12380/308741
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectFinite element modelling
dc.subjectLithium-ion battery
dc.subjectFailure models
dc.subjectCrash simulations
dc.subjectMaterial behaviour
dc.subjectElectric vehicle
dc.subjectAnisotropic materia
dc.subjectShort-circuit prediction
dc.subjectParametric optimisation
dc.titlePredicting short circuit of Li-ion battery cells during mechanical abuse
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster's Thesisen
dc.type.uppsokH
local.programmeApplied mechanics (MPAME), MSc
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