EV Energy Master: AI for Smarter Electric Vehicle Charging Patterns

inAI & Emerging Technologies

Background

This project enables students to explore artificial intelligence (AI), data science, and sustainable energy strategies by addressing the growing challenge of electric vehicle (EV) charging optimization. As the adoption of EVs rises, efficiently managing charging patterns becomes vital for both consumers and energy providers. This project aims to develop an AI system that predicts EV charging behavior to ease energy demand during peak hours and enhance power usage efficiency.

Learning Outcome (LO)

  • LO #1: AI in Smart Energy Management 
    Gain insights into AI-driven energy management in smart grids, learning techniques like load forecasting and demand-side management that predict and regulate EV charging. 
  • LO #2: Data Analysis for EV Behaviour
    Acquire skills in analysing factors influencing EV charging, such as time-of-day, location, and user preferences, to understand patterns in consumer charging behaviour.
  • LO #3: Sustainable Energy Solutions 
    Understand how load balancing and predictive modeling can improve energy distribution and support sustainable growth in EV infrastructure.

What is on offer?

  • 1-on-1 sessions with Ph.D. Scholars
  • Supervision and Guidance from Global Faculty
  • Assistance in Publishing Research
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