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AI Driven Battery Management System - A Review
Subject area: Science,Engineering and Technology · Area of research: Electric Vehicles
Abstract
This paper presents about BMS with fire detection and accident alert systems for enhanced safety. The proposed system integrates several features like checking battery health, fire safety using raspberry pi, accident alert system using ADXL-345, GIM SIM8001 and GPS Neo-6m. The system utilizes Arduino UNO microcontroller and displays relevant information on an LCD. This multi-layered approach aims to significantly enhance fire safety and driver safety
Keywords
bms, gps, GIM SIM8001, PPS Neo-6m, ADXL 335 sensor.
How to cite this paper
Pranita Sanjeev Shetty, Kushal Raj K, Prof. Gopal Chandra Sarkar , Awab Ahmed Shariff, Mohammed Shabaz Delvi "AI Driven Battery Management System - A Review" Iconic Research And Engineering Journals Volume 8 Issue 12 2025 Page 416-423
Pranita Sanjeev Shetty, Kushal Raj K, Prof. Gopal Chandra Sarkar , Awab Ahmed Shariff, Mohammed Shabaz Delvi "AI Driven Battery Management System - A Review" Iconic Research And Engineering Journals, vol. 8, no. 12, Jun. 2025
Pranita Sanjeev Shetty, Kushal Raj K, Prof. Gopal Chandra Sarkar , Awab Ahmed Shariff, Mohammed Shabaz Delvi (2025). AI Driven Battery Management System - A Review. Iconic Research And Engineering Journals, 8(12).
Pranita Sanjeev Shetty, Kushal Raj K, Prof. Gopal Chandra Sarkar , Awab Ahmed Shariff, Mohammed Shabaz Delvi "AI Driven Battery Management System - A Review" Iconic Research And Engineering Journals, vol. 8, no. 12, Jun. 2025.
@article{1708987,
author = {Pranita Sanjeev Shetty, Kushal Raj K, Prof. Gopal Chandra Sarkar , Awab Ahmed Shariff, Mohammed Shabaz Delvi},
title = {AI Driven Battery Management System - A Review},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {12},
pages = {416-423},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708987.pdf},
abstract = {This paper presents about BMS with fire detection and accident alert systems for enhanced safety. The proposed system integrates several features like checking battery health, fire safety using raspberry pi, accident alert system using ADXL-345, GIM SIM8001 and GPS Neo-6m. The system utilizes Arduino UNO microcontroller and displays relevant information on an LCD. This multi-layered approach aims to significantly enhance fire safety and driver safety},
keywords = {bms, gps, GIM SIM8001, PPS Neo-6m, ADXL 335 sensor.},
month = {June},
}