Electric Vehicles (EVs) are often hailed as the future of green mobility, yet one concern continues to ignite doubts—battery fires. From sudden overheating to unpredictable thermal runaway, these incidents not only endanger users but also slow down EV adoption. What if there were a way to foresee and prevent such risks before they turned dangerous? Enter IITGN’s AI tool, a breakthrough innovation designed to act like a health monitor for EV batteries. By predicting hidden threats and ensuring safer performance, this tool could be the game-changer India needs for reliable and worry-free electric transportation.
Tackling EV Safety with AI
The IITGN tool leverages “conformal prediction”, an advanced AI technique that goes beyond traditional machine learning models. Unlike older methods that provide a single temperature estimate, this system offers a range of possible temperature predictions, making it more reliable under changing conditions such as:
- Battery age and usage patterns
- Environmental factors like heat and humidity
- Mechanical stress from road vibrations
By delivering multiple scenarios instead of one rigid output, the tool allows EV systems to better prepare for potential risks.
Key Features of the IITGN AI Tool
- Range-based Predictions – Provides possible ranges for battery temperature rather than a single number, ensuring more accurate monitoring.
- Battery Aging Adaptability – Maintains reliability throughout the entire battery lifespan, unlike traditional models that degrade over time.
- Thermal Management Support – Accurately detects potential overheating events, enabling better cooling and fire prevention mechanisms.
- High Accuracy – In tests, nearly 79% of real battery temperatures were found to be within the predicted range, demonstrating its effectiveness.
A “Health Monitoring System” for Batteries
Prof. Pallavi Bharadwaj, who leads the development team, explains that the tool functions like a “smartwatch for EV batteries.” Just as a smartwatch tracks vital signs of the human body, this system continuously monitors temperature, voltage, pressure, and gas release inside the battery.
The system uses sensors and AI-powered digital twins—virtual replicas of real batteries—that help identify stress and overheating long before visible damage occurs. Once a risk is detected, alerts can be sent directly to the vehicle dashboard or a remote monitoring system, giving drivers enough time to act before the situation escalates.
Broader Safety Research at IITGN
This innovation is part of a larger initiative by IITGN’s Centre for Safety Engineering, which is working on:
- Studying lithium-ion battery behavior under electrical, thermal, and mechanical stress.
- Developing early-warning methods to detect thermal runaway precursors (the chain reaction leading to fire).
- Supporting the creation of national EV safety standards in line with AIS 156 and AIS 038 Rev 2 regulations.
Designed for Indian Conditions
EVs in India face unique challenges such as high temperatures, humidity, and rough road conditions. The IITGN system is built specifically for these environments, making it cost-effective and easily adoptable by local manufacturers.
Funded under the Mission for Advancement in High-Impact Areas (MAHA) for EVs, this project aims not only to prevent fires but also to extend battery lifespan, lower ownership costs, and build public trust in electric mobility.
Towards Safer EVs
By combining AI, sensors, and digital models, IITGN’s tool works like a “doctor for batteries”—diagnosing issues before they become dangerous. With such technologies, India is not just solving local EV safety problems but also developing solutions that can be exported globally.
This innovation could become a turning point in making EVs safer, more reliable, and truly future-ready for millions of users.
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