Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. The precise SOC estimation confirms the safety and reliability of EV. Neverthel...
Saved in:
Main Authors: | Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M. |
---|---|
Other Authors: | 58562396100 |
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2024
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
by: Dickson Neoh Tze How, Dr.
Published: (2023) -
A Study on Heat Generation of Lithium-Ion Battery Used in Electric Vehicles by Simulation and Experiment
by: Selvararajoo K., et al.
Published: (2024) -
Cathode materials for high energy density rechargeable lithium-ion batteris
by: Gan, Kian Chao
Published: (2017) -
Investigating on nanofluid based thermal management system for 18650 lithium-ion batery module with fixed contact surface
by: Goo Wei Hong
Published: (2023) -
Lithium-ion battery charge equalization algorithm for electric vehicle applications
by: M.A Hannan
Published: (2017)