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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68121
Volume:
10 |
10 |
Oct 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
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.
E&TC Engineering
JSPM’s B. P. Polytechnic
E&TC Engineering
JSPM’s B. P. Polytechnic
E&TC Engineering
JSPM’s B. P. Polytechnic
E&TC Engineering
JSPM’s B. P. Polytechnic
E&TC Engineering
JSPM’s B. P. Polytechnic
Electric vehicles (EVs) depend on rechargeable battery packs whose safety, available energy, and service life are strongly influenced by monitoring and control. This review examines the main functions relevant to a smart EV battery management system (BMS), with emphasis on voltage and current measurement, temperature supervision, state-ofcharge (SOC) estimation, Internet of Things (loT)-enabled remote monitoring, overcharge protection, and theft alerts. The supplied project synopsis proposes an Arduino UNO controller, voltage/current/temperature and vibration sensors, an ESP8266 Wi-Fi module, an LCD, a relay, and a Blynk dashboard. The paper organizes these elements into a systemlevel architecture, discusses the potential benefits and implementation limitations, and identifies practical issues that must be addressed before deployment in a real vehicle. The review is based on the supplied synopsis and its listed references; it does not claim experimental validation or measured performance. In particular, temperature alarms are treated as an early-warning function rather than a complete fire-suppression solution, and a vibration sensor is considered a basic tamper indicator rather than proof of theft. The paper concludes with research directions in battery state estimation, cell balancing, robust communications, thermal-risk detection, and secure vehicle monitoring.
KEYWORDS
Artificial Intelligence and Machine Learning: Future systems can use AI and machine learning algorithms to analyze battery data, predict possible faults, and identify abnormal operating conditions before serious problems occur.2.Predictive Battery Maintenance: Advanced monitoring techniques can estimate battery degradation and predict maintenance requirements, helping to reduce unexpected failures and improve battery life. 3.Advanced Thermal Management: Future systems can integrate intelligent cooling mechanisms, advanced temperature sensors, and early fault detection methods to improve thermal safety and reduce the risk of battery overheating.
1. G. Jayabharathi, A. SB, S. Kalimuthu, M. Mohamed Fazil, and N. Dinesh Kumar, “Smart EV Battery Management System with IoT-Based Monitoring, Fire and Theft Protection,” International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), vol. 5, no. 2, May 2025.DOI: 10.48175/IJARSCT-26282 2. “Towards Safer and Smarter Design for Lithium-IonBattery-Powered Electric Vehicles: A Comprehensive Review on Control Strategy Architecture of Battery Management System,” Energies, vol. 15, no. 12, 2022. Read the article 3. S. K. Mulpuri, B. Sah, and P. Kumar, “An Intelligent Battery Management System (BMS) with End-EdgeCloud Connectivity – A Perspective,” Sustainable Energy & Fuels, vol. 9, pp. 1142–1159, 2025. DOI: 10.1039/D4SE01238K 5. “A Review of IoT-Enhanced Battery Management Systems for Electric Vehicles: Trends, Architectures, and Industrial Insights,” in Proceedings of the 5th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 2025.10.1109/ICECCME64568.2025.11277959 DOI:
Publication Date
10/19/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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