State of Charge Estimation for Lithium-Ion Batteries at Various Temperatures by Extreme Gradient Boosting and Adaptive Cubature Kalman Filter-Reference-Cited by-同舟云学术

State of Charge Estimation for Lithium-Ion Batteries at Various Temperatures by Extreme Gradient Boosting and Adaptive Cubature Kalman Filter

Published:2024 Issue: Volume:73 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Hou Weilu¹^ORCID,Shi Qin¹^ORCID,Liu Yiwen¹^ORCID,Guo Liquan¹^ORCID,Zhang Xiaonan¹^ORCID,Wu Ji¹^ORCID

Affiliation:

1. School of Automotive and Transportation Engineering and the Engineering Research Center for Intelligent Transportation and Cooperative Vehicle-Infrastructure of Anhui Province, Hefei University of Technology, Hefei, China

Funder

University Synergy Innovation Program of Anhui Province

Innovation Project of New Energy Vehicle and Intelligent Connected Vehicle of Anhui Province

Fundamental Research Funds for the Central Universities of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10373171.pdf?arnumber=10373171

Reference36 articles.

1. A review of recent developments in renewable and sustainable energy systems: Key challenges and future perspective

2. A brief review on key technologies in the battery management system of electric vehicles

3. A framework for state-of-charge and remaining discharge time prediction using unscented particle filter

4. State of Charge Estimation of Power Lithium-ion Battery Based on a Variable Forgetting Factor Adaptive Kalman Filter

5. IC Curve-Based Lithium-Ion Battery SOC Estimation at High Rate Charging Current

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