Conference
A Comparison Study of Unidirectional and Bidirectional Recurrent Neural Network for Battery State of Charge Estimation
Abstract
An accurate state of charge (SOC) estimation is important for ensuring the safe operation of electric vehicles (EVs). Recurrent Neural Networks (RNNs), known for their time-sequence capabilities, offer advantages in battery SOC estimation. Bidirectional RNNs (BiRNN), in particular, have recently been introduced in this domain. Conventional testing methods for BiRNN often utilize the entire dataset, allowing the model to access future data for …
Authors
Yao Q; Kollmeyer PJ; Lu DD-C; Emadi A
Volume
00
Pagination
pp. 1-6
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
June 21, 2024
DOI
10.1109/itec60657.2024.10598937
Name of conference
2024 IEEE Transportation Electrification Conference and Expo (ITEC)