AI POWDERED EV OPTIMIZATION

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  Workflow of project

Inspiration

The project was inspired by the rapid growth of electric vehicles in India and the need for smarter tools to improve battery efficiency, charging convenience, and overall EV performance. We wanted to build a system that helps both drivers and EV companies make data-driven decisions.

What We Learned

While working on this project, we learned how AI can significantly improve EV range and performance. We also explored how automation tools like n8n simplify data collection and workflow management, and how environmental factors like traffic, temperature, and terrain affect battery usage.

How We Built It

We combined machine learning models with n8n automated workflows to collect and process real-time data such as driving patterns, battery health, weather, and charging availability. The insights generated by the AI are then used to recommend optimal charging times, efficient driving routes, and smart battery management.

Challenges We Faced

Some major challenges included gathering clean EV data, handling regional variations across India, integrating multiple APIs in n8n, and ensuring the system works fast enough to deliver real-time recommendation

Built With

• gemini
• google
• n8n
• twilio