Lithium battery state of health prediction method based on online knee point warning identification of coupling temperature
Author:
Affiliation:
1. School of Mathematics and Statistics, Xidian University,Xi'an,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10482420/10482375/10482505.pdf?arnumber=10482505
Reference28 articles.
1. State of Health Assessment of Lithium-ion Batteries Based on Deep Gaussian Process Regression Considering Heterogeneous Features
2. Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach
3. Multi-Segment State of Health Estimation of Lithium-ion Batteries Considering Short Partial Charging
4. State of health estimation of large-cycle lithium-ion batteries based on error compensation of autoregressive model
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