SOC estimation for lithium‐ion batteries based on a novel model
Author:
Affiliation:
1. National Engineering Laboratory for Highway Maintenance Equipment Chang'an University Xi'an China
2. Henan Gaoyuan Maintenance Technology of Highway Co. Ltd. Xinxiang China
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/pel2.12175
Reference24 articles.
1. Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li‐S case studies
2. A Novel State Estimation Approach Based on Adaptive Unscented Kalman Filter for Electric Vehicles
3. Iterative learning based model identification and state of charge estimation of lithium‐ion battery;Zhu Q.;IET Power Electron,2019
4. Adaptive State-of-Charge Estimation Based on a Split Battery Model for Electric Vehicle Applications
5. State‐of‐charge estimation of lithium‐ion batteries using composite multi‐dimensional features and a neural network
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