Modellierung von Lithium-Ionen-Batterien zur Lebensdauerprädiktion unter besonderer Berücksichtigung des Anodenüberhangeffekts
The focus of this work is on the modelling of the degradation behaviour of conventional lithium-ion cells with graphite/NMC electrodes in conjunction with electrolytes based on LiPF6 in organic solvents. The potential for improvements of parameterization methods dealing with physical-chemical aging...
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| Format: | Electronic Book Chapter |
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Karlsruhe
KIT Scientific Publishing
2022
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| Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 100 | 1 | |a Philipp Fath, Johannes |4 auth | |
| 245 | 1 | 0 | |a Modellierung von Lithium-Ionen-Batterien zur Lebensdauerprädiktion unter besonderer Berücksichtigung des Anodenüberhangeffekts |
| 260 | |a Karlsruhe |b KIT Scientific Publishing |c 2022 | ||
| 300 | |a 1 electronic resource (346 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a The focus of this work is on the modelling of the degradation behaviour of conventional lithium-ion cells with graphite/NMC electrodes in conjunction with electrolytes based on LiPF6 in organic solvents. The potential for improvements of parameterization methods dealing with physical-chemical aging effects and simulation studies for optimization of the battery lifetime is shown. In the process of model parameterization mostly data-based as well as non-invasive analysis methods are used. | ||
| 540 | |a Creative Commons |f by-sa/4.0 |2 cc |4 http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a German | ||
| 650 | 7 | |a Mechanical engineering & materials |2 bicssc | |
| 653 | |a Lithium-Ionen-Zelle | ||
| 653 | |a Batterie | ||
| 653 | |a Elektrofahrzeug | ||
| 653 | |a Degradationsmechanismen | ||
| 653 | |a Lebensdauerprädiktion | ||
| 653 | |a lithium-ion cell | ||
| 653 | |a battery | ||
| 653 | |a electric vehicle | ||
| 653 | |a degradation mechanism | ||
| 653 | |a lifetime prediction | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/id/01aacfdf-3c45-490d-811a-f97b7a30f2f0/9783731511397.pdf |7 0 |z OAPEN Library: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/53522 |7 0 |z OAPEN Library: description of the publication |