Projects per year
Abstract
Nowadays, lithium-ion batteries are the predominant energy storage technology for vehicles with electrified drive trains. In case of an accident mechanical loads on Li-ion cells may cause an internal shortcircuit which can further lead to severe exothermic reactions (e.g. smoke, fire, explosion). Existing numerical methods to estimate the time-dependent mechanical, electrical and thermal processes are not sufficient at present. For that reason a novel approach has been developed. Three major parts - explicit non-linear structural analysis (FEA), implicit multi-physical simulation and an interface to link these two simulation tools - have been combined to form a continuous work-flow. While the FEA model has been set up using a microscopic scale mesh, the multi-physics code was extended by a short-circuit model. This approach is capable of predicting the cell behaviour due to crash loads (e.g. acceleration, deformation).
Original language | English |
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Title of host publication | EVS 2017 - 30th International Electric Vehicle Symposium and Exhibition |
Publication status | Published - 2017 |
Event | 30th International Electric Vehicle Symposium and Exhibition: EVS 2017 - Stuttgart, Germany Duration: 9 Oct 2017 → 11 Oct 2017 http://www.messe-stuttgart.de/en/evs30 |
Conference
Conference | 30th International Electric Vehicle Symposium and Exhibition |
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Country/Territory | Germany |
City | Stuttgart |
Period | 9/10/17 → 11/10/17 |
Internet address |
Fields of Expertise
- Mobility & Production
Fingerprint
Dive into the research topics of 'Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads'. Together they form a unique fingerprint.Projects
- 1 Finished
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13_FFG_EinBliC - Development of a multi-physics computational model of Li-ion cells as the basis for increasing battery crash safety
Breitfuß, C.
1/07/13 → 31/12/15
Project: Research project
Activities
- 1 Talk at conference or symposium
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Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads
Simon Franz Heindl (Speaker)
10 Oct 2017Activity: Talk or presentation › Talk at conference or symposium › Science to science
Research output
- 1 Paper
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Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads
Heindl, S. F., 10 Oct 2017.Research output: Contribution to conference › Paper › peer-review