Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments

Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments

The increasing interests and recent advancements in artificial intelligence and machine learning have significantly accelerated the development of novel techniques for the state estimation of batteries in electrified vehicles’ battery management systems (BMSs). Determining the remaining capacity amo...

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Bibliographic Details
Main Authors: Uzair Khan, Mohd Tariq, Arif I. Sarwat
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Energies
Subjects:
state of charge
estimation battery management system
SOC
machine learning
genetic algorithm
energy storage
Online Access:https://www.mdpi.com/1996-1073/17/22/5582
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