Estimation Accuracy and Computational Cost Analysis of Artificial Neural Networks for State of Charge Estimation in Lithium Batteries

Estimation Accuracy and Computational Cost Analysis of Artificial Neural Networks for State of Charge Estimation in Lithium Batteries

This paper presents a tradeoff analysis in terms of accuracy and computational cost between different architectures of artificial neural networks for the State of Charge (SOC) estimation of lithium batteries in hybrid and electric vehicles. The considered layouts are partly selected from the literat...

Full description

Bibliographic Details
Main Authors: Angelo Bonfitto, Stefano Feraco, Andrea Tonoli, Nicola Amati, Francesco Monti
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Batteries
Subjects:
state of charge
estimation
artificial neural networks
computational cost
Lithium battery
electric vehicles
Online Access:https://www.mdpi.com/2313-0105/5/2/47

Similar Items

Similar Items