Intelligent recognition of structural health state of EV lithium-ion Battery using transfer learning based on X-ray computed tomography
Author:
Funder
National Natural Science Foundation of China
Beijing Municipal Science and Technology Commission
Publisher
Elsevier BV
Reference42 articles.
1. Prognostics and health management of lithium-ion battery using deep learning methods: A review;Zhang;Renew Sustain Energy Rev,2022
2. IC curve-based lithium-ion battery SOC estimation at high rate charging current;Yu;IEEE Trans Instrum Meas,2022
3. Real-time state-of-health monitoring of lithium-ion battery with anomaly detection, Levenberg–Marquardt algorithm, and multiphase exponential regression model;Ossai;Neural Comput Appl,2021
4. Analysis of gas production in overcharged lithium battery by X-ray computed tomography;Zhang;J Electrochem Energy Convers Stor,2021
5. Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis;Meng;Reliab Eng Syst Saf,2023
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