Fast Charging Li-Ion Battery Capacity Fade Prognostic Modeling Using Correlated Parameters' Decomposition and Recurrent Wavelet Neural Network-Reference-Cited by-同舟云学术

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Fast Charging Li-Ion Battery Capacity Fade Prognostic Modeling Using Correlated Parameters' Decomposition and Recurrent Wavelet Neural Network

Published:2021-06-21 Issue: Volume: Page:
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Container-title:2021 IEEE Transportation Electrification Conference & Expo (ITEC)
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Author:

Khalid Asadullah,Sarwat Arif I.

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9490020/9490033/09490177.pdf?arnumber=9490177

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analysis on the Thermal Behavior of Lithium-Ion Battery with Nickel-Rich Cathode and Silicon-Carbon Composite Anode;SAE International Journal of Electrified Vehicles;2023-11-21

2. Unraveling capacity fading in lithium-ion batteries using advanced cyclic tests: A real-world approach;iScience;2023-10

3. Degradation Evaluation of Lithium-Ion Batteries in Plug-In Hybrid Electric Vehicles: An Empirical Calibration;Batteries;2023-06-10

4. Sizing and Lifecycle Assessment of Electrochemical Batteries for Electric Vehicles and Renewable Energy Storage Systems;Smart Mobility - Recent Advances, New Perspectives and Applications;2023-05-24

5. A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms;Energies;2023-03-31

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