Estimation of State of Charge of EV Batteries-A Machine Learning Approach

Author:

Upashrutti A1,Thampatty K. C. Sindhu1

Affiliation:

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

Publisher

IEEE

Reference14 articles.

1. Support Vector Regression;basak;Electrical and Instrumentation Department,2007

2. State of charge (SoC) estimation of LiFePO4 battery module using support vector regression

3. Model Based Fault Classification Method for Electric Vehicle Pertained Lithium-Ion Batteries Using Multi Layer Perceptron,0

4. Estimation of SOC and SOH Using Mixed Neural Network and Coulomb Counting Algorithm;shanmughasundaram,2019

5. Machine Learning Based Battery Aging Management Strategy for Electric Vehicles;bibinsha;IEEE Xplore,2021

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1. Analysis of Various Types of Battery Systems On APU for More Electric Aircraft;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

2. Advancing State of Charge Management in Electric Vehicles With Machine Learning: A Technological Review;IEEE Access;2024

3. A Comprehensive Exploration on Different Machine Learning Techniques for State of Charge Estimation of EV Battery;2023 58th International Universities Power Engineering Conference (UPEC);2023-08-30

4. Operation characteristics and performance analysis of integrated power and hybrid cooling systems driven by PEM fuel cell;International Journal of Hydrogen Energy;2023-04

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