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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
Elsevier
2024
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/41124/ 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 |
Internet
http://umpir.ump.edu.my/id/eprint/41124/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