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Intelligent Battery Management Systems for Electric Vehicles Using AI and Internet of Things Technologies
Authors
1 2 3 4 UG Scholar, Department of Electrical and Electronics Engineering, Holy Mary Institute of Technology and Science, Hyderabad, Telangana, India. 5 Assistant Professor, Department of Electrical and Electronics Engineering, Holy Mary Institute of Technology and Science, Hyderabad, Telangana, India.
Article Information
- DOI
- No Doi
- Published In
- Year 2025 · Volume 2 · Issue 3
- Published Online
- September-December 2025
- Pages
- 24-27
- Article Type
- Original Article
- Check for updates
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References
1. A. Farmann, D. U. Sauer, and M. Waag, "Machine Learning Approaches for Battery State Estimation in Electric Vehicles," Journal of Energy
Storage, vol. 44, pp. 103-118, 2022.
2. Y. Zhang, X. Wang, and H. He, "Artificial Intelligence-Based Battery Management Systems for Electric Mobility Applications," IEEE
Transactions on Transportation Electrification, vol. 9, no. 2, pp. 1120–1135, 2023.
3. X. Liu, Y. Wang, and H. He, "Deep Learning Techniques for Battery Health Prediction and Remaining Useful Life Estimation," IEEE Access,
vol. 11, pp. 45210–45230, 2023.
4. N. Sharma, A. Verma, and S. Singh, "IoT-Enabled Battery Monitoring and Predictive Maintenance Framework for Electric Vehicles," Energy
Reports, vol. 10, pp. 1820–1838, 2024.
5. Y. Li, F. Qiu, and J. Wang, "Artificial Intelligence-Assisted Battery Management and Charging Optimization for Electric Vehicles," Applied
Energy, vol. 356, pp. 121–142, 2024.
6. K. Patel and R. Mehta, "Advanced AI-Based Battery Diagnostics and Prognostics for Electric Mobility Systems," Sustainable Energy
Technologies and Assessments, vol. 63, pp. 103–126, 2025.
7. M. Rahman, S. Islam, and T. Ahmed, "Intelligent Battery Management Framework Using IoT and Deep Learning Technologies," Energy AI,
vol. 15, pp. 100–122, 2025.
8. J. Chen, X. Li, and Y. Sun, "Digital Twin-Enabled Battery Management Systems for Future Electric Vehicles," IEEE Access, vol. 13, pp.
45120–45145, 2025.
Storage, vol. 44, pp. 103-118, 2022.
2. Y. Zhang, X. Wang, and H. He, "Artificial Intelligence-Based Battery Management Systems for Electric Mobility Applications," IEEE
Transactions on Transportation Electrification, vol. 9, no. 2, pp. 1120–1135, 2023.
3. X. Liu, Y. Wang, and H. He, "Deep Learning Techniques for Battery Health Prediction and Remaining Useful Life Estimation," IEEE Access,
vol. 11, pp. 45210–45230, 2023.
4. N. Sharma, A. Verma, and S. Singh, "IoT-Enabled Battery Monitoring and Predictive Maintenance Framework for Electric Vehicles," Energy
Reports, vol. 10, pp. 1820–1838, 2024.
5. Y. Li, F. Qiu, and J. Wang, "Artificial Intelligence-Assisted Battery Management and Charging Optimization for Electric Vehicles," Applied
Energy, vol. 356, pp. 121–142, 2024.
6. K. Patel and R. Mehta, "Advanced AI-Based Battery Diagnostics and Prognostics for Electric Mobility Systems," Sustainable Energy
Technologies and Assessments, vol. 63, pp. 103–126, 2025.
7. M. Rahman, S. Islam, and T. Ahmed, "Intelligent Battery Management Framework Using IoT and Deep Learning Technologies," Energy AI,
vol. 15, pp. 100–122, 2025.
8. J. Chen, X. Li, and Y. Sun, "Digital Twin-Enabled Battery Management Systems for Future Electric Vehicles," IEEE Access, vol. 13, pp.
45120–45145, 2025.
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