Battery state of charge estimation based on a combined model of Extended Kalman Filter and neural networks
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx5/6022827/6033131/06033495.pdf?arnumber=6033495
Cited by 62 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An optimized quantum particle swarm optimization–extended Kalman filter algorithm for the online state of charge estimation of high-capacity lithium-ion batteries under varying temperature conditions;Ionics;2024-08-06
2. Advanced State of Charge Estimation Using Deep Neural Network, Gated Recurrent Unit, and Long Short-Term Memory Models for Lithium-Ion Batteries under Aging and Temperature Conditions;Applied Sciences;2024-07-30
3. Enhancing Estimating the Charge Level in Electric Vehicles: Leveraging Force Fluctuation and Regenerative Braking Data;International Journal of Innovative Science and Research Technology (IJISRT);2024-07-16
4. Review on Battery State Estimation and Management Solutions for Next-Generation Connected Vehicles;Energies;2023-12-29
5. Review of Management System and State-of-Charge Estimation Methods for Electric Vehicles;World Electric Vehicle Journal;2023-11-27
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