A Battery Modeling Technique Based on Fusion of Hybrid and Adaptive Algorithms for Real-Time Applications in Pure EVs-Reference-Cited by-同舟云学术

A Battery Modeling Technique Based on Fusion of Hybrid and Adaptive Algorithms for Real-Time Applications in Pure EVs

Published:2023-03 Issue:3 Volume:24 Page:2760-2771
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Moulik Bedatri¹^ORCID,Dubey Ashwani Kumar²^ORCID,Ali Ahmed M.³^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, Uttar Pradesh, India

2. Department of Electronics and Communication Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, Uttar Pradesh, India

3. Automotive Engineering Department, Military Technical College, Cairo, Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10057093/09966313.pdf?arnumber=9966313

Reference41 articles.

1. Lithium-Ion Battery Modeling Including Degradation Based on Single-Particle Approximations

2. End-of-discharge and End-of-life Prediction in Lithium-ion Batteries with Electrochemistry-based Aging Models

3. A new life estimation method for lithium-ion batteries in plug-in hybrid electric vehicles applications

4. Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications

5. Comparison of State-of-Charge (SOC) estimation performance based on three popular methods: Coulomb counting, open circuit voltage, and Kalman filter

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