Balancing accuracy and efficiency: a homogeneous ensemble approach for lithium-ion battery state of charge estimation in electric vehicles-Reference-Cited by-同舟云学术

Balancing accuracy and efficiency: a homogeneous ensemble approach for lithium-ion battery state of charge estimation in electric vehicles

Published:2024-08-02 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Wong Rae Hann,Sooriamoorthy Denesh^ORCID,Manoharan Aaruththiran,Binti Sariff Nohaidda,Hilmi Ismail Zool

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00521-024-10210-5.pdf

Reference38 articles.

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3. A Manoharan and KM Begam (2023) Investigation on multiphase multistage bidirectional DC-DC converter for electric vehicles using virtual vehicle driving platform. In: 2023 IEEE 17th international conference on industrial and information systems, ICIIS 2023 – proceedings. pp. 275–280. https://doi.org/10.1109/ICIIS58898.2023.10253526

4. Maisel F, Neef C, Marscheider-Weidemann F, Nissen NF (2023) A forecast on future raw material demand and recycling potential of lithium-ion batteries in electric vehicles. Resour Conserv Recycl 192:106920. https://doi.org/10.1016/j.resconrec.2023.106920

5. Li C, Xiao F, Fan Y (2019) An approach to state of charge estimation of lithium-ion batteries based on recurrent neural networks with gated recurrent unit. Energies 12(9):1592. https://doi.org/10.3390/en12091592