A Novel IoT-Driven Battery Management System with Automated Fire Protection for Enhanced Electric Vehicle Safety

Abstract

Electric vehicle safety has become a critical concern due to the increasing use of lithium-ion batteries, which are susceptible to overheating, thermal runaway, and fire hazards under abnormal operating conditions. This study presents a novel IoT-driven Battery Management System integrated with an automated CO? fire suppression mechanism for enhanced electric vehicle safety. The proposed system continuously monitors key battery parameters including voltage, current, and temperature through dedicated sensors connected to an Arduino-based control unit. Real-time data acquisition and IoT communication enable remote monitoring and instant fault notifications. When abnormal temperature rise, overcharging, or unsafe operating conditions are detected, the system automatically disconnects the battery using a relay-based protection circuit to prevent further damage. In critical situations involving fire detection, a solenoid-actuated CO? cylinder is triggered to suppress flames rapidly and minimize the risk of battery propagation. The integration of battery monitoring, fault protection, IoT connectivity, and automatic fire suppression improves operational reliability, battery lifespan, and user safety. Experimental evaluation demonstrates effective fault detection, timely protective actions, and enhanced protection for electric vehicle battery systems.

Introduction

The rapid adoption of electric vehicles (EVs) as a sustainable transportation solution has increased the importance of battery safety, reliability, and efficient energy management. Electric vehicles reduce pollution, greenhouse gas emissions, and dependence on fossil fuels while offering advantages such as high efficiency, lower maintenance, and reduced operating costs. However, lithium-ion batteries used in EVs face challenges such as overheating, overcharging, excessive current, deep discharge, and internal short circuits, which can lead to battery degradation, thermal runaway, fires, and safety hazards.

A Battery Management System (BMS) is essential for maintaining battery health by continuously monitoring parameters such as voltage, current, temperature, and state of charge. With the integration of Internet of Things (IoT) technology, modern BMS solutions can provide real-time monitoring, remote access, fault detection, predictive maintenance, and instant alerts.

This study proposes an IoT-driven Battery Management System integrated with an automated CO? fire suppression mechanism to improve electric vehicle safety. The system continuously monitors battery conditions using sensors and intelligent control circuits. When abnormal conditions such as overheating or electrical faults are detected, protective relays isolate the battery, and a CO?-based fire suppression system activates automatically to prevent fire spread.

The literature review highlights advancements in EV battery safety through IoT, artificial intelligence, machine learning, thermal management, and fire protection systems. Previous research shows that real-time monitoring and intelligent control improve battery efficiency, fault detection, reliability, and safety. However, many existing systems lack integrated fire suppression and rapid emergency response capabilities.

The main problem addressed is the risk of lithium-ion battery failures caused by thermal stress, electrical faults, and delayed detection. The proposed system aims to:

• Continuously monitor battery voltage, current, and temperature
• Detect abnormal conditions early
• Prevent overcharging, deep discharge, overheating, and short circuits
• Enable remote monitoring through IoT connectivity
• Provide automatic fire protection using CO? suppression
• Improve EV battery lifespan, reliability, and user safety

The proposed methodology consists of six major stages:

1. Battery Parameter Monitoring:
   Sensors continuously measure voltage, current, and temperature to assess battery operating conditions and identify early signs of failure.
2. Battery Management and Protection Control:
   The controller analyzes sensor data and activates protection mechanisms such as battery isolation during unsafe conditions.
3. IoT-Based Communication and Remote Monitoring:
   Battery data is transmitted through IoT modules to remote platforms, enabling real-time monitoring, alerts, and historical analysis.
4. Thermal Runaway and Fire Detection:
   Temperature and fire sensors identify overheating and possible thermal runaway events before they become dangerous.
5. Automated CO? Fire Suppression:
   During fire or critical temperature events, a solenoid valve releases CO? to suppress flames by reducing oxygen availability. CO? is suitable because it is non-conductive and leaves no residue.
6. System Integration and Safety Response:
   The complete system combines sensing, monitoring, protection, IoT communication, and fire suppression into one safety framework.

The experimental prototype includes an Arduino-based BMS, IoT communication module, voltage and temperature sensors, lithium-ion battery pack, LCD display, and CO? suppression unit. The system provides real-time battery monitoring, automatic fault response, and emergency fire protection.

Conclusion

In this research, a novel IoT-driven Battery Management System with automated CO? fire suppression was presented to enhance the safety, reliability, and operational efficiency of electric vehicle battery systems. The proposed framework integrated voltage, current, and temperature monitoring with intelligent protection mechanisms to continuously supervise battery conditions and identify abnormal operating states. Real-time data acquisition and IoT connectivity enabled remote monitoring and instant fault notifications, improving system awareness and response capabilities. The battery management unit effectively protected the battery pack from overcharging, excessive discharge, overheating, and other hazardous conditions that could affect performance and lifespan. Furthermore, the incorporation of an automated CO? fire suppression mechanism provided an additional layer of protection against thermal runaway and battery fire incidents. The integrated architecture demonstrated improved battery safety, reduced operational risks, and enhanced system reliability. Future work can focus on incorporating advanced machine learning algorithms for predictive fault detection and battery health estimation. Cloud-based analytics and digital twin technologies may further improve monitoring accuracy and maintenance planning. The integration of additional gas, smoke, and thermal imaging sensors can strengthen fire detection capabilities, while scalable battery management architectures can support larger electric vehicle platforms and next-generation energy storage systems.

References

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Copyright

Copyright © 2026 Asst. Prof. Ashwini Yenegur , Pooja ., Varsha D. H., Pavitra ., Varsha R.. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.