AI Driven Battery Management System - A Review
  • Author(s): Pranita Sanjeev Shetty ; Kushal Raj K ; Prof. Gopal Chandra Sarkar ; Awab Ahmed Shariff ; Mohammed Shabaz Delvi
  • Paper ID: 1708987
  • Page: 416-423
  • Published Date: 11-06-2025
  • Published In: Iconic Research And Engineering Journals
  • Publisher: IRE Journals
  • e-ISSN: 2456-8880
  • Volume/Issue: Volume 8 Issue 12 June-2025
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.

Citations

IRE Journals:
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

IEEE:
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, 8(12)