Health prognostics framework of lithium-ion batteries for real-world electric vehicles based on charging data
Author:
Affiliation:
1. Xihua University,Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, School of Automobile and Transportation,Chengdu,China,610039
Funder
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10567049/10567050/10567846.pdf?arnumber=10567846
Reference16 articles.
1. Degradation Behavior of Lithium-Ion Batteries Based on Lifetime Models and Field Measured Frequency Regulation Mission Profile
2. One-shot battery degradation trajectory prediction with deep learning
3. Battery Lifetime Prognostics
4. Co-estimation of state of charge and state of health for lithium-ion batteries based on fractional-order model with multi-innovations unscented Kalman filter method
5. Coestimation of State-of-Charge and State-of-Health for Power Batteries Based on Multithread Dynamic Optimization Method
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