Optimally Tuned Gated Recurrent Unit Neural Network-Based State of Health Estimation Scheme for Lithium Ion Batteries-Reference-Cited by-同舟云学术

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Optimally Tuned Gated Recurrent Unit Neural Network-Based State of Health Estimation Scheme for Lithium Ion Batteries

Published:2024 Issue: Volume:12 Page:58597-58607
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rao K. Dhananjay¹^ORCID,Anand N. Vijaya²,Pandraju T. Krishna Sai³,Alsaif Faisal⁴^ORCID,Ustun Taha Selim⁵^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, India

2. Department of Electrical Electronics Engineering, PVP Siddhartha Institute of Technology, Vijayawada, India

3. Department of Electrical Electronic Engineering, Dhanekula Institute of Engineering and Technology, Vijayawada, India

4. Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia

5. Fukushima Renewable Energy Institute, AIST (FREA), Koriyama, Japan

Funder

Researchers Supporting Project number

King Saud University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10506507.pdf?arnumber=10506507

Reference32 articles.

1. Comparison of lead-acid and lithium ion batteries for stationary storage in off-grid energy systems

2. Robust Observer Design for Mitigating the Impact of Unknown Disturbances on State of Charge Estimation of Lithium Iron Phosphate Batteries Using Fractional Calculus

3. A Comparative Review on Energy Storage Systems and Their Application in Deregulated Systems

4. Fractional order modeling based optimal multistage constant current charging strategy for lithium iron phosphate batteries

5. A review of the state of health for lithium-ion batteries: Research status and suggestions

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1. A hybrid battery degradation model combining arrhenius equation and neural network for capacity prediction under time-varying operating conditions;Reliability Engineering & System Safety;2024-12

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