State-of-Charge Estimation of Medium- and High-Voltage Batteries Using LSTM Neural Networks Optimized with Genetic Algorithms

This study presents a hybrid method for state-of-charge (SOC) estimation of lithium-ion batteries using LSTM neural networks optimized with genetic algorithms (GA), combined with Coulomb Counting (CC) as an initial estimator. Experimental tests were conducted using medium-voltage (48–72 V) lithium-i...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 25; no. 15; p. 4632
Main Authors:	Carrera, Romel, Quiroz, Leonidas, Guevara, Cesar, Acosta-Vargas, Patricia
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 26.07.2025 MDPI
Subjects:	Accuracy Batteries Deep learning Electric vehicles Embedded systems Genetic algorithms Lithium Machine learning monitoring system Neural networks Optimization Parameter identification SOC estimation Support vector machines vehicle range SOC estimation genetic algorithms monitoring system vehicle range
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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