Study on Artificial Intelligence-Driven Development of Sodium-Ion Battery Materials and Battery Configuration in Electric Vehicles

Article Citation : Varun Kumar , Dnyaneshwar Ramchandra Waghole , Vaibhav Vijay Kulkarni , (2026) "Study on Artificial Intelligence-Driven Development of Sodium-Ion Battery Materials and Battery Configuration in Electric Vehicles", International Journal of Industrial Electronics and Electrical Engineering (IJIEEE) , pp. 16-21, Volume-14,Issue-6

Abstract : The growing demand for electric vehicles has created a need for efficient, affordable, and sustainable battery technologies. Sodium-ion batteries are considered a promising alternative to lithium-ion batteries due to the availability and low cost of sodium. This study explores the use of artificial intelligence (AI) in developing sodium-ion battery materials and optimizing battery configurations for electric vehicles. AI techniques help improve battery performance, energy efficiency, charging speed, and lifespan. The study highlights the potential of AI-driven optimization in designing safer, more reliable, and cost-effective battery systems for future electric vehicles. Keywords - Artificial Intelligence, Sodium-Ion Batteries, Electric Vehicles, Machine Learning, Battery Materials, Battery Configuration, Energy Storage, Battery Optimization

Type : Research paper

Published : Volume-14,Issue-6