State of Charge Estimation for EV Batteries Using Support Vector Regression

Author:

Jumah Sarah1,Elezab Ahmed1,Zayed Omar1,Ahmed Ryan2,Narimani Mehdi1,Emadi Ali1

Affiliation:

1. McMaster University,Departement of Electrical and Computer Engineering,Hamilton,Canada

2. McMaster University,Departement of Mechanical Engineering,Hamilton,Canada

Publisher

IEEE

Cited by 14 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. Evaluating Solar Power Forecasting Robustness: A Comparative Analysis of XGBoost, RNN, KNN, RF, and LSTM with emphasis on Lagged Steps, Sensitivity, and Cross-Validation Techniques;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06

2. Enhanced SOC estimation of lithium ion batteries with RealTime data using machine learning algorithms;Scientific Reports;2024-07-11

3. Comparative Study of Levenberg-Marquardt and Scaled Conjugate Gradient Algorithms for Estimating Battery State of Charge;2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT);2024-07-04

4. SoC Estimation for an Electric Two-Wheeler Using Machine Learning Techniques;2024 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE);2024-02-16

5. Predicting AGV Battery Cell Voltage Using a Neural Network Approach with Preliminary Data Analysis and Processing;2023 IEEE International Conference on Big Data (BigData);2023-12-15

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