State of Charge and State of Health Estimation for Lithium Batteries Using Recurrent Neural Networks

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 10; pp. 8773 - 8783
• Main Authors: Chaoui, Hicham, Ibe-Ekeocha, Chinemerem Christopher
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aging; Ambient temperature; Batteries; Discharges (electric); Electric vehicles; Estimation; Intelligence; lifetime estimation; Lithium; Lithium batteries; neural networks; Power management; Rechargeable batteries; Recurrent neural networks; Robustness (mathematics); State of charge; state of health; Temperature measurement; Vehicle dynamics; Voltage measurement

This paper presents an application of dynamically driven recurrent networks (DDRNs) in online electric vehicle (EV) battery analysis. In this paper, a nonlinear autoregressive with exogenous inputs (NARX) architecture of the DDRN is designed for both state of charge (SOC) and state of health (SOH) e...