State of Charge Estimation in Lithium-Ion Batteries: A Neural Network Optimization Approach

• Published in: Electronics (Basel) Vol. 9; no. 9; p. 1546
• Main Authors: Hossain Lipu, M. S., Hannan, M. A., Hussain, Aini, Ayob, Afida, Saad, Mohamad H. M., Muttaqi, Kashem M.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2020
• Subjects: Accuracy; Aging; Algorithms; Aluminum oxide; Back propagation; Bias; Charge efficiency; Climate change; Cobalt oxides; Electric vehicles; Fault diagnosis; Heuristic methods; Lithium; Lithium-ion batteries; Manganese; Network management systems; Neural networks; Nickel; Noise; Optimization; Optimization techniques; Rechargeable batteries; Root-mean-square errors; State of charge; Time lag

The development of an accurate and robust state-of-charge (SOC) estimation is crucial for the battery lifetime, efficiency, charge control, and safe driving of electric vehicles (EV). This paper proposes an enhanced data-driven method based on a time-delay neural network (TDNN) algorithm for state o...