Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads

Publikation: KonferenzbeitragAbstractForschungBegutachtung

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).
Originalspracheenglisch
PublikationsstatusAngenommen/In Druck - 24 Apr 2017
VeranstaltungEVS30 Symposium: Electric Vehicle Symposium & Exhibition - Stuttgart, Deutschland
Dauer: 9 Okt 201711 Okt 2017
http://www.messe-stuttgart.de/en/evs30

Konferenz

KonferenzEVS30 Symposium
LandDeutschland
OrtStuttgart
Zeitraum9/10/1711/10/17
Internetadresse

Fingerprint

Finite element method
Exothermic reactions
Smoke
Structural analysis
Short circuit currents
Energy storage
Interfaces (computer)
Explosions
Telecommunication links
Numerical methods
Accidents
Fires
Physics
Ions
Lithium-ion batteries
Hot Temperature

Fields of Expertise

  • Mobility & Production

Dies zitieren

Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads. / Heindl, Simon Franz; Breitfuß, Christoph; Greimel, Robert; Sinz, Wolfgang; Ellersdorfer, Christian; Feist, Florian; Fink, Clemens.

2017. Abstract von EVS30 Symposium, Stuttgart, Deutschland.

Publikation: KonferenzbeitragAbstractForschungBegutachtung

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T1 - Introducing an approach to predict the time-dependent mechanical, electrical and thermal behaviour of Li-ion batteries due to crash loads

AU - Heindl, Simon Franz

AU - Breitfuß, Christoph

AU - Greimel, Robert

AU - Sinz, Wolfgang

AU - Ellersdorfer, Christian

AU - Feist, Florian

AU - Fink, Clemens

PY - 2017/4/24

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N2 - 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).

AB - 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).

M3 - Abstract

ER -