A method based on improved ant lion optimization and support vector regression for remaining useful life estimation of lithium‐ion batteries
Author:
Affiliation:
1. School of Automation Engineering Northeast Electric Power University Jilin China
2. State Grid Jibei Electric Power CO., LTD, Research Institute Beijing China
3. State Grid Jilin Electric Power CO., LTD Jilin China
Funder
National Natural Science Foundation of China
Publisher
Wiley
Subject
General Energy,Safety, Risk, Reliability and Quality
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.460
Reference38 articles.
1. Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
2. Remaining Useful Life Prediction of Lithium-Ion Batteries Using Support Vector Regression Optimized by Artificial Bee Colony
3. Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
4. A hybrid model based on support vector regression and differential evolution for remaining useful lifetime prediction of lithium-ion batteries
5. Battery Health Prognosis Using Brownian Motion Modeling and Particle Filtering
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