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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65517

IOT BASED BATTERY MANAGEMENT SYSTEM FOR ELECTRIC VEHICLE

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65517

Volume:

10 |

6 |

Jun 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65517

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SJK

Sushant Jayram Kshirsagar

Electrical Engineering

Dr. V. V. P. college of engineering, ahilyanagar

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AS

Akshay Sinare

Electrical Engineering

Dr. V. V. P. college of engineering, ahilyanagar

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SJ

Shantanu Jadhav

Electrical Engineering

Dr. V. V. P. college of engineering, ahilyanagar

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DSS

Dr. S.K. Sheikh

Electrical Engineering

Dr. V. V. P. college of engineering, ahilyanagar

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SH

Sarthak Hulge

Electrical Engineering

Dr. V. V. P. college of engineering, ahilyanagar

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Abstract

The Battery Management System (BMS) is one of the most important components in Electric Vehicles (EVs) and battery-powered energy storage systems. It plays a vital role in ensuring the safety, reliability, and efficient operation of battery packs. As the demand for electric vehicles continues to increase worldwide, the need for advanced battery monitoring and protection systems has become more significant. A BMS continuously monitors important battery parameters such as voltage, current, temperature, state of charge (SOC), and state of health (SOH). By tracking these parameters, the system helps maintain the battery within safe operating limits and improves its overall performance and lifespan One of the major challenges associated with battery systems is the risk of overheating, overcharging, deep discharging, and short circuits, which can lead to battery degradation or even fire accidents. To address these issues, the proposed system incorporates a burning prevention mechanism that detects abnormal battery conditions at an early stage. Temperature sensors are used to monitor the thermal condition of the battery in real time. When the battery temperature exceeds a predefined threshold value, the system immediately disconnects the battery output using a protection relay and activates a buzzer to alert the user. This rapid response helps prevent thermal runaway and reduces the risk of battery fires. The proposed IoT-based Battery Monitoring and Burning Prevention System provides continuous monitoring of a lead-acid battery and stores key operating parameters, including battery voltage, charging and discharging current, temperature, state of charge, and remaining battery capacity. A Wireless Local Area Network (WLAN) serves as the communication backbone, enabling real-time transmission of battery data to a central monitoring platform. The collected information from multiple battery nodes is analyzed to identify abnormal operating conditions and potential faults. Users can remotely access battery status through an IoT interface, making it easier to monitor battery health and performance from any location. The system offers enhanced safety, improved battery life, reduced maintenance costs, and better energy management. It is particularly useful in electric vehicles, renewable energy storage systems, UPS units, and industrial battery banks. By integrating real-time monitoring, fault detection, IoT connectivity, and automatic protection features, the proposed system provides a reliable and intelligent solution for battery management and fire prevention, contributing to the safe and efficient utilization of modern battery technologies.

KEYWORDS

Battery Management System (BMS) Electric Vehicle (EV) Internet of Things (IoT) Lead-Acid Battery State of Charge (SOC) Thermal Protection Battery Monitoring Fire Prevention.

Cite This Article

Sushant Jayram Kshirsagar, Akshay Sinare, Shantanu Jadhav, Dr. S.K. Sheikh, Sarthak Hulge, "IOT BASED BATTERY MANAGEMENT SYSTEM FOR ELECTRIC VEHICLE," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-7, Jun 2026. https://doi.org/10.55041/IJSREM65517

Full Article/Conclusion

The IoT-based Battery Management System (BMS) provides an effective solution for monitoring and managing battery performance through real-time data acquisition and communication. The system continuously tracks important battery parameters such as voltage, temperature, and operational status to ensure safe and efficient battery usage. Experimental results indicate that battery voltage decreases during the discharge process, while temperature gradually increases with prolonged operation. Through IoT technology, the collected data can be remotely monitored and analyzed for improved system control. The proposed system enhances battery reliability, enables early fault detection, reduces maintenance requirements, improves battery lifespan, and supports efficient energy utilization, making it suitable for various smart energy and industrial applications. The increasing demand for electric vehicles (EVs) due to the depletion of fossil fuels has made battery technology and battery management systems (BMS) essential components of modern transportation. Since the performance, reliability, and safety of an electric vehicle depend entirely on its battery, continuous monitoring and proper management of battery parameters are necessary for efficient operation. The proposed IoT-based Battery Management System provides an effective solution for monitoring battery performance in real time. By continuously measuring important parameters such as voltage, current, temperature, and state of charge, the system helps maintain the battery within safe operating limits. The integration of IoT technology enables remote monitoring, allowing users and operators to access battery information from anywhere through an internet-connected device. A significant advantage of the proposed system is its ability to detect abnormal battery conditions and degraded battery performance at an early stage. When any parameter exceeds the predefined threshold value, the system generates notifications and alerts, enabling timely corrective actions. This feature helps prevent battery damage, improves operational safety, and reduces the possibility of unexpected failures. Furthermore, the inclusion of temperature monitoring and protection mechanisms enhances battery safety by reducing the risk of overheating and fire hazards. The collected data can also be stored and analzed for predictive maintenance and performance evaluation. Overall, the IoT-based Battery Management System improves battery efficiency, extends battery life, enhances vehicle safety, and reduces maintenance costs. Therefore, it represents a reliable and intelligent solution for future electric vehicles and energy storage applications, supporting the growth of sustainable and environmentally friendly transportation systems.

References

[1]    Hemaprithni R. and G. T. Sundar Rajan, “Three Level Integrated AC to DC Converter fed DC Drive with Cascaded Filter,” International Journal of Applied Engineering Research, Vol. 10, No. 6, pp. 5140–5146, 2015.   [2]       Senthil Nayagam V., G. T. Sundar Rajan and V. Balasubramanian, “Improved Power Factor at Input Stage of Pseudo Boost Rectifier with Improved Switching Pattern,” International Journal of Applied Engineering Research, Vol. 10, No. 6, pp. 5158–5164, 2015.   [3]   Sundar Rajan G. T. and C. Christober Asir Rajan, “A Novel Unity Power Factor Input Stage with Resonant DC Link Inverter for AC Drives,” Journal of Electrical Engineering, Vol. 12, No. 4, pp. 62–66, 2012.     [4]   Sundar Rajan G. T., “Power Quality Improvement at Input and Output Stages of Three Phase Diode Rectifier using Artificial Intelligent Techniques for DC and AC Drive Applications,” IEEE ICCIC, pp. 904–909, 2014.   [5]   Venkatasetty H. V. and Y. U. Jeong, “Recent Advances in Lithium-Ion and Lithium-Polymer Batteries,” 17th Annual Battery Conference on Applications and Advances, pp. 173–178, 2002.   [6]    Wu C., J. L. Sun, C. B. Zhu, Y. W. Ge and Y. P. Zhao, “Research on Overcharge and Overdischarge Effect on Lithium-Ion Batteries,” IEEE Vehicle Power and Propulsion Conference, pp. 1–6, 2015. [7]     Yong Tian, Dong Li and Jindong Tian, “An Optimal Nonlinear Observer for State-of-Charge Estimation of Lithium-Ion Batteries,” IEEE ICIEA, 2017.   [8]   Gregory L. Plett, “Extended Kalman Filtering for Battery Management Systems of LiPB-Based HEV Battery Packs,” Journal of Power Sources, Vol. 134, No. 2, pp. 252–261, 2004. [9]   M. A. Hannan, M. M. Hoque, A. Mohamed and A. Ayob, “Review of Energy Storage Systems for Electric Vehicle Applications,” Renewable and Sustainable Energy Reviews, Vol. 69, pp. 771–789, 2017   [10]  N. Williard, W. He, C. Hendricks and M. Pecht, “Lessons Learned from the 787 Dreamliner Issue on Lithium-Ion Battery Reliability,” Energies, Vol. 6, No. 9, pp. 4682–4695, 2013.

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Publication Date

6/26/2026

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Review Rounds: 2

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