State of Energy Prediction of Lithium-ion Battery Using Sparrow Search Optimization-Random Forest and State-of-the-Art Artificial Intelligence Methods
Author:
- 7 October 2025
- journal article
- research article
- Published by Springer Nature in Journal of Electrical Engineering & Technology
- Vol. 21 (2) , 1873-1887
Abstract
No abstract availableKeywords
This publication has 57 references indexed in Scilit:
- A Systematic Review of the Whale Optimization Algorithm: Theoretical Foundation, Improvements, and HybridizationsArchives of Computational Methods in Engineering, 2023
- A review of renewable energy based power supply options for telecom towersEnvironment, Development and Sustainability, 2023
- A Comprehensive Review of Bat Inspired Algorithm: Variants, Applications, and HybridizationArchives of Computational Methods in Engineering, 2022
- A state‐of‐health estimation method considering capacity recovery of lithium batteriesInternational Journal of Energy Research, 2022
- Advances in Sparrow Search Algorithm: A Comprehensive SurveyArchives of Computational Methods in Engineering, 2022
- Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problemsInternational Journal of Intelligent Systems, 2021
- A novel framework for lithium‐ion battery state of charge estimation based on Kalman filter Gaussian process regressionInternational Journal of Energy Research, 2021
- Lithium‐ionbatterySOC/SOHadaptive estimation via simplified single particle modelInternational Journal of Energy Research, 2020
- Random forest regression for online capacity estimation of lithium-ion batteriesApplied Energy, 2018
- The Whale Optimization AlgorithmAdvances in Engineering Software, 2016