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• W2917885700 abstract "This work presents a prediction of battery terminal voltage in subsequent charging/discharging cycles. To estimate chosen signals the NARX (AutoRegressive with eXogenous input) model based on Recurrent Neural Network has been employed. A training and testing data were gathered at the laboratory test stand with the Lithium Iron Phosphate (LiFePO4) battery in different working conditions. Test stand research was conducted for 40 charging/discharging cycles. Furthermore, the paper presents the results of the identification of double RC model parameters for a specified state of charge level. As a result, the analysis of the proposed methodology has been discussed." @default.
• W2917885700 created "2019-03-02" @default.
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• W2917885700 date "2019-02-16" @default.
• W2917885700 modified "2023-09-26" @default.
• W2917885700 title "Battery Voltage Estimation Using NARX Recurrent Neural Network Model" @default.
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• W2917885700 doi "https://doi.org/10.1007/978-3-030-13273-6_22" @default.
• W2917885700 hasPublicationYear "2019" @default.
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