Unified Univariate-Neural Network Models for Lithium-Ion Battery State-of-Charge Forecasting Using Minimized Akaike Information Criterion Algorithm

Unified Univariate-Neural Network Models for Lithium-Ion Battery State-of-Charge Forecasting Using Minimized Akaike Information Criterion Algorithm

Lithium-Ion batteries require step-ahead information to apply contingency plans to prevent them from operating beyond their safe operation thresholds in grid storage and electric vehicle applications. Recently, machine learning techniques have been increasingly applied to forecast one such battery i...

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Bibliographic Details
Main Authors: Asadullah Khalid, Arif I. Sarwat
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Lithium-ion
univariate ARIMA
HWES
NARX
MLP
state-of-charge forecasting
Online Access:https://ieeexplore.ieee.org/document/9360803/

Internet

https://ieeexplore.ieee.org/document/9360803/

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