A hybrid model for state of charge estimation of lithium-ion batteries utilizing improved adaptive extended Kalman filter and long short-term memory neural network
Author:
Funder
National Natural Science Foundation of China
Hunan Provincial Natural Science Foundation
Publisher
Elsevier BV
Reference46 articles.
1. State of health estimation of lithium-ion batteries with a temporal convolutional neural network using partial load profiles;Bockrath;Appl. Energy,2023
2. An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation;Liu;Appl. Energy,2022
3. State of health estimation for lithium-ion battery based on energy features;Gong;Energy,2022
4. The Co-estimation of state of charge, state of health, and state of function for lithium-ion batteries in electric vehicles;Shen;IEEE Trans. Veh. Technol.,2018
5. Combined state of charge and state of energy estimation of lithium-ion battery using dual forgetting factor-based adaptive extended Kalman filter for electric vehicle applications;Shrivastava;IEEE Trans. Veh. Technol.,2021
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