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State of charge estimation for electric vehicles using random forest

This paper introduces an innovative approach to addressing a critical challenge in the electric vehicle (EV) industry—the accurate estimation of the state of charge (SOC) of EV batteries under real-world operating conditions. The electric mobility landscape is rapidly evolving, demanding more precis...

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Bibliographic Details
Main Authors: Mohd Herwan, Sulaiman, Zuriani, Mustaffa
Format: Article
Language:English
English
Published: Elsevier 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41124/1/State%20of%20charge%20estimation%20for%20electric%20vehicles%20using%20random%20forest.pdf
http://umpir.ump.edu.my/id/eprint/41124/7/State%20of%20charge%20estimation%20for%20electric%20vehicles%20using%20random%20forest.pdf
http://umpir.ump.edu.my/id/eprint/41124/
https://doi.org/10.1016/j.geits.2024.100177
https://doi.org/10.1016/j.geits.2024.100177
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http://umpir.ump.edu.my/id/eprint/41124/1/State%20of%20charge%20estimation%20for%20electric%20vehicles%20using%20random%20forest.pdf
http://umpir.ump.edu.my/id/eprint/41124/7/State%20of%20charge%20estimation%20for%20electric%20vehicles%20using%20random%20forest.pdf
http://umpir.ump.edu.my/id/eprint/41124/
https://doi.org/10.1016/j.geits.2024.100177
https://doi.org/10.1016/j.geits.2024.100177

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