Aging prediction and state of charge estimation of a LiFePO4 battery using input time-delayed neural networks

•Achieve both SOC and SOH estimation under aging and temperature uncertainties.•This technique requires no prior knowledge of the battery's model or parameters.•Effectiveness is validated experimentally.•Comparison against conventional MLP. This paper presents an intelligent state of charge (SO...

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Veröffentlicht in:	Electric power systems research 2017-05, Vol.146, p.189-197
Hauptverfasser:	Chaoui, Hicham, Ibe-Ekeocha, Chinemerem C., Gualous, Hamid
Format:	Artikel
Sprache:	eng
Schlagworte:	Aging Ambient temperature Artificial neural network (ANN) Batteries Electrochemical analysis Input time-delayed neural network (ITDNN) Lithium Lithium iron phosphate (LiFePO4) Lithium-ion batteries Neural networks Open circuit voltage (OCV) Rechargeable batteries Root mean squared error (RMSE) State of charge State of charge (SOC) State of health (SOH)
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