State of Charge (SoC) Determination Through Extended Kalman Filter in Battery Management Systems-Reference-Cited by-同舟云学术

State of Charge (SoC) Determination Through Extended Kalman Filter in Battery Management Systems

Published:2023-09-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Region 10 Symposium (TENSYMP)
language:
Short-container-title:

Author:

Padalale Namrata¹,Sindhu M. R.²

Affiliation:

1. Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapeetham,Department of Electronics and Communication Engineering,India

2. Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapeetham,Department of Electrical and Electronics Engineering,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10223594/10223477/10223676.pdf?arnumber=10223676

Reference21 articles.

1. Recent progress and future trends on state of charge estimation methods to improve battery-storage efficiency: A review

2. State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge

3. Comparative Analysis of Passive and Active Cell Balancing of Li Ion Batteries

4. State of charge estimation of the lithium ion battery using an adaptive extended kalman filter based on an improved thevenin model;he;IEEE Transactions on Vehicular Technology,2011

5. Estimation Techniques for State of Charge in Battery Management Systems on Board of Hybrid Electric Vehicles Implemented in a Real-Time MATLAB/SIMULINK Environment

Cited by 1 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. Enhanced lithium–ion battery state of charge estimation in electric vehicles using extended Kalman filter and deep neural network;International Journal of Dynamics and Control;2024-02-21