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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Autores principales:	Sara Luciani, Stefano Feraco, Angelo Bonfitto, Andrea Tonoli
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	battery monitoring system state of charge artificial neural networks hardware-in-the-loop real-time hardware modeling Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/d4debc727c9646eeaa79fbff5aa501f1
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Hardware-in-the-Loop Assessment of a Data-Driven State of Charge Estimation Method for Lithium-Ion Batteries in Hybrid Vehicles

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