Lithium-Ion Battery Aging Analysis of an Electric Vehicle Fleet Using a Tailored Neural Network Structure

Thomas Lehmann, Frances Weiß

Open source

DOI: 10.3390/app13074448
Published: 03
Container: Applied Sciences
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/app13074448,
  title = {Lithium-Ion Battery Aging Analysis of an Electric Vehicle Fleet Using a Tailored Neural Network Structure},
  author = {Thomas Lehmann and Frances Weiß},
  year = {2023},
  journal = {Applied Sciences},
  doi = {10.3390/app13074448},
  url = {https://doi.org/10.3390/app13074448}
}

RIS

TY  - JOUR
TI  - Lithium-Ion Battery Aging Analysis of an Electric Vehicle Fleet Using a Tailored Neural Network Structure
AU  - Thomas Lehmann
AU  - Frances Weiß
PY  - 2023
JO  - Applied Sciences
DO  - 10.3390/app13074448
UR  - https://doi.org/10.3390/app13074448
ER  -

APA

Lehmann, T., & Weiß, F. (2023). Lithium-Ion Battery Aging Analysis of an Electric Vehicle Fleet Using a Tailored Neural Network Structure. Applied Sciences. https://doi.org/10.3390/app13074448

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doaj · retrieved 2026-09-26T08:52:17.922Z