Optimizing fault diagnosis for electric vehicle battery systems: Improved Giza pyramids construction and advanced gradient boosting decision trees-Reference-Cited by-同舟云学术

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Optimizing fault diagnosis for electric vehicle battery systems: Improved Giza pyramids construction and advanced gradient boosting decision trees

Published:2024-03 Issue: Volume:81 Page:110319
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Subramaniyan R.

Publisher

Elsevier BV

Reference50 articles.

1. Propagation mechanisms and diagnosis of parameter inconsistency within Li-ion battery packs;Feng;Renew. Sust. Energ. Rev.,2019

2. A novel fault diagnosis method for lithium-ion battery packs of electric vehicles;Li;Measurement,2018

3. A multi-fault diagnostic method based on an interleaved voltage measurement topology for series connected battery packs;Kang;J. Power Sources,2019

4. A correlation based fault detection method for short circuits in battery packs;Xia;J. Power Sources,2017

5. A novel active equalization method for lithium-ion batteries in electric vehicles;Wang;Appl. Energy,2015

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