Call for Paper, 25 August 2026. Please submit your manuscript via online system or email at editor@ijew.io

ISSN E 2409-2770
ISSN P 2521-2419

AI-Driven Smart Electric Vehicles: A Revolutionary Paradigm Shift in Sustainable Transportation


Shah Muhammad Adan, Md. Mudassir Chowdhury, Muhammad Abobakar Sadiq, Daloar Hossan, Khan Jawad, Muhammad Tahir Zaman


Vol. 13, Issue 06, PP. 39-49 June 2026

DOI

Keywords: Artificial intelligence, electric vehicles, autonomous driving, predictive maintenance, smart charging infrastructure, ethical AI

Download PDF


The Artificial Intelligence (AI) integration into Electric Vehicles (EVs) is revolutionizing automotive industry by solving critical problems related to sustainable transportation. This comprehensive review examines the revolutionary impact of AI applications in EVs, focusing on four key domains: capabilities of autonomous driving, sophisticated smart charging infrastructure, state of the art in battery management systems and predictive maintenance. It describes how by analyzing current implementations and future technologies, AI native solutions ensure energy efficiency, enhanced safety protocol, optimized user experience and reduce environmental impacts. First, the paper conducts a critical exploration of ethical issues in AI, including data privacy, algorithmic bias, and accident accountability, and draws up frameworks for robust deployment of responsible AI systems. Finally, the paper also touches on the future ideas of V2G technology being used in a real life scenario, developing Level 5 autonomous vehicles and eco-driving systems and how they can possibly be implemented for higher sustainability and better human machine environment cooperation. Deep diving into technical advancements and ethical implications, they take a closer look at how AI powered EVs can quickly put the world on track for a green transportation revolution with responsible technological deployment.


  1. Shah Muhammad Adnan, , College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, Jiangsu, China.
  2. Md Mudassir Chowdhury, , College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, Jiangsu, China.
  3. Muhammad Abobakar Sadiq, , College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, Jiangsu, China.
  4. Daloar Hossan, , College of Information and Artificial Intelligence, Yangzhou University, Yangzhou, 225012, China.
  5. Khan Jawad, , School of Electrical and Automation Engineering. Nanjing Normal University, China.
  6. Muhammad Tahir Zaman, , School of Mechanical Engineering, Southeast University, Nanjing210096, China.

Shah Muhammad Adnan Md Mudassir Chowdhury Muhammad Abobakar Sadiq Daloar Hossan Khan Jawad Muhammad Tahir Zaman “AI-Driven Smart Electric Vehicles: A Revolutionary Paradigm Shift in Susta Vol. 13 Issue 06 PP. 39-49 June 2026. https://doi.org/10.5281/zenodo.21550138.


[1]     M. Ahmed, Y. Zheng, A. Amine, H. Fathiannasab, and Z. Chen, “The role of artificial intelligence in the mass adoption of electric vehicles,” Joule, vol. 5, no. 9, pp. 2296–2322, 2021.

[2]     J. K. Verma, R. Kanday, and S. Gupt, “Role of artificial intelligence in revolutionizing the automotive industry: A review,” in E3S Web of Conferences, vol. 556, p. 01039, EDP Sciences, 2024.

[3]     E. Lukin, A. Krajnovic, and J. Bosna, “Sustainability strategies and´ achieving sdgs: A comparative analysis of leading companies in the automotive industry,” Sustainability, vol. 14, no. 7, p. 4000, 2022.

[4]     H. Rehan, “The future of electric vehicles: Navigating the intersection of ai, cloud technology, and cybersecurity,” Valley International Journal Digital Library, pp. 1127–1143, 2024.

[5]     M. Mosayebi, M. Gheisarnejad, H. Farsizadeh, B. Andresen, and M. H. Khooban, “Smart extreme fast portable charger for electric vehiclesbased artificial intelligence,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 70, no. 2, pp. 586–590, 2022.

[6]     V. Sumanasena, L. Gunasekara, S. Kahawala, N. Mills, D. De Silva, M. Jalili, S. Sierla, and A. Jennings, “Artificial intelligence for electric vehicle infrastructure: Demand profiling, data augmentation, demand forecasting, demand explainability and charge optimisation,” Energies, vol. 16, no. 5, p. 2245, 2023.

[7]     M. H. Lipu, M. S. Miah, T. Jamal, T. Rahman, S. Ansari, M. S. Rahman, R. H. Ashique, A. Shihavuddin, and M. N. Shakib, “Artificial intelligence approaches for advanced battery management system in electric vehicle applications: A statistical analysis towards future research opportunities,” Vehicles, vol. 6, no. 1, pp. 22–70, 2023.

[8]     X. Wu, B. Cao, J. Wen, and Y. Bian, “Particle swarm optimization for plug-in hybrid electric vehicle control strategy parameter,” in 2008 IEEE Vehicle Power and Propulsion Conference, pp. 1–5, IEEE, 2008.

[9]     M. H. Abbasi, Z. Arjmandzadeh, J. Zhang, B. Xu, and V. Krovi, “Deep reinforcement learning based fast charging and thermal management optimization of an electric vehicle battery pack,” Journal of Energy Storage, vol. 95, p. 112466, 2024.

[10]  S. P. Mahardhika and O. Putriani, “A review of artificial intelligenceenabled electric vehicles in traffic congestion management,” in ICSEDTI 2022: Proceedings of the 1st International Conference on Sustainable Engineering Development and Technological Innovation, ICSEDTI 2022, 11-13 October 2022, Tanjungpinang, Indonesia, p. 255, European Alliance for Innovation, 2023