This paper presents some experiences and results obtained about the problem of the SOC and voltage prediction and simulation of new generation batteries. A complex pipelined recurrent neural network (PRNN) was designed for modeling of new generation batteries storage in order to predict the SOC and the terminal voltage. The simulation results are compared with experimental data obtained on commercial batteries.

Hybrid neural networks architectures for SOC and voltage prediction of new generation batteries storage

CAPIZZI, GIACOMO;NAPOLI, CHRISTIAN
2011-01-01

Abstract

This paper presents some experiences and results obtained about the problem of the SOC and voltage prediction and simulation of new generation batteries. A complex pipelined recurrent neural network (PRNN) was designed for modeling of new generation batteries storage in order to predict the SOC and the terminal voltage. The simulation results are compared with experimental data obtained on commercial batteries.
2011
978-142448928-2
Neural Networks; Modelling; Simulations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/93965
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