Artificial Intelligence based State of Charge estimation of Li-ion battery for EV applications
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9130794/9137848/09137999.pdf?arnumber=9137999
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. Investigation of maximum temperatures in lithium-ion batteries by CFD and machine learning;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2024-04-12
2. Artificial intelligence driven hydrogen and battery technologies – A review;Fuel;2023-04
3. Unified Approach for Estimation of State of Charge and Remaining Useful Life of Li-Ion batteries using Deep Learning;2022 IEEE 19th India Council International Conference (INDICON);2022-11-24
4. Comparative Analysis on Deep Learning Methods to Estimate the State of Charge in Li-ion Battery;2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon);2022-10-16
5. State of charge, remaining useful life and knee point estimation based on artificial intelligence and Machine learning in lithium-ion EV batteries: A comprehensive review;Renewable Energy Focus;2022-09
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