Showing results 1 to 5 of 5
A Robust State of Charge Estimation Approach Based on Nonlinear Battery Cell Model for Lithium-Ion Batteries in Electric Vehicles Kim, Wooyong; Lee, Pyeong-Yeon; Kim, Jonghoon; Kim, Kyung-Soo, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.70, no.6, pp.5638 - 5647, 2021-06 |
Composition and state prediction of lithium-ion cathode via convolutional neural network trained on scanning electron microscopy images Oh, Jimin; Yeom, Jiwon; Madika, Benediktus; Kim, Kwang Man; Liow, Chi Hao; Agar, Joshua C; Hong, Seungbum, NPJ COMPUTATIONAL MATERIALS, v.10, no.1, 2024-05 |
Online Remaining Useful Life Prediction for Lithium-Ion Batteries Using Partial Discharge Data Features Ali, Muhammad Umair; Zafar, Amad; Nengroo, Sarvar Hussain; Hussain, Sadam; Park, Gwan-Soo; Kim, Hee-Je, ENERGIES, v.12, no.22, 2019-11 |
Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation Ali, Muhammad Umair; Zafar, Amad; Nengroo, Sarvar Hussain; Hussain, Sadam; Alvi, Muhammad Junaid; Kim, Hee-Je, ENERGIES, v.12, no.3, pp.446, 2019-02 |
Two-stage deep learning for online prediction of knee-point in Li-ion battery capacity degradation Sohn, Suyeon; Byun, Ha-Eun; Lee, Jay Hyung, APPLIED ENERGY, v.328, 2022-12 |
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