Deep learning-based EV battery fault diagnosis using RBBMO with CAR-TATNET detection approach.

Tamizharasi G, Rajini GK

DOI: 10.3389/frai.2026.1876996
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.3389/frai.2026.1876996,
  title = {Deep learning-based EV battery fault diagnosis using RBBMO with CAR-TATNET detection approach.},
  author = {Tamizharasi G and Rajini GK},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1876996},
  url = {https://doi.org/10.3389/frai.2026.1876996}
}

RIS

TY  - JOUR
TI  - Deep learning-based EV battery fault diagnosis using RBBMO with CAR-TATNET detection approach.
AU  - Tamizharasi G
AU  - Rajini GK
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1876996
UR  - https://doi.org/10.3389/frai.2026.1876996
ER  -

APA

G, T., & GK, R. (2026). Deep learning-based EV battery fault diagnosis using RBBMO with CAR-TATNET detection approach.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1876996

Source records

pubmed · retrieved 2026-09-25T21:18:59.863Z