Hardware-in-the-Loop Assessment of a Data-Driven State of Charge Estimation Method for Lithium-Ion Batteries in Hybrid Vehicles

Hardware-in-the-Loop Assessment of a Data-Driven State of Charge Estimation Method for Lithium-Ion Batteries in Hybrid Vehicles

This paper presents the design and hardware-in-the-loop (HIL) experimental validation of a data-driven estimation method for the state of charge (<i>SOC</i>) in the lithium-ion batteries used in hybrid electric vehicles (HEVs). The considered system features a 1.25 kWh 48 V lithium-ion b...

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Bibliographic Details
Main Authors: Sara Luciani, Stefano Feraco, Angelo Bonfitto, Andrea Tonoli
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Electronics
Subjects:
battery monitoring system
state of charge
artificial neural networks
hardware-in-the-loop
real-time hardware
modeling
Online Access:https://www.mdpi.com/2079-9292/10/22/2828

Internet

https://www.mdpi.com/2079-9292/10/22/2828

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