Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63614
Volume:
10 |
5 |
May 2026
Pages:
1-5
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.
Department of electrical engineering
Nansaheb Madhik College Of Engineering Peth
Department of electrical engineering
Nansaheb Madhik College Of Engineering Peth
Department of electrical engineering
Nansaheb Madhik College Of Engineering Peth
Department of electrical engineering
Nansaheb Madhik College Of Engineering Peth
As the automotive industry shifts toward sustainable transport, the efficiency and safety of Energy Storage Systems (ESS) have become paramount. This paper presents the development of a robust Battery Management System (BMS) designed for a 12-series connected Lithium-ion battery pack. Utilizing the LTC6804-2 multicell battery stack monitor, the system provides precise monitoring of overvoltage, undervoltage, overcurrent, and thermal irregularities. The hardware architecture, designed via Eagle CAD, integrates a PIC microcontroller for data processing and a custom balance board to ensure cell longevity. Preliminary results indicate high reliability in fault detection and cell equalization, addressing the critical requirements of safety and autonomy in modern Electric Vehicles (EVs).
KEYWORDS
The project successfully developed a MATLAB/Simulink-based Battery Management System for electric vehicles. It effectively monitors battery parameters like voltage, current, temperature, SOC, and SOH, ensuring safe and reliable operation. The simulation demonstrates battery protection, fault detection, and performance monitoring without hardware complexity. This model serves as a strong foundation for learning and future enhancements. With features like hardware implementation, CAN communication, and advanced algorithms, the system can be extended for real-time EV applications, improving battery efficiency and lifespan.
1. Pragya Raghav & Khalil Ur Rehman, “A review of Battery Management System for EV: Estimation and Types,” IJIREEICE, 2025. 2. M. T. M. N. et al., “Evaluation of Battery Management Systems for Electric Vehicles Using Traditional and Modern Estimation Methods,” MDPI, 2025. 3. Yuan Xueqing et al., “Battery Management System for Electric Vehicle and the Study of SOC Estimation,” AASRI Conference, 2015. 4. Ming Jiang et al., “Advances in Battery State Estimation of Battery Management System in Electric Vehicles,” Journal of Power Sources, 2024.. A Systematic Literature Review of State of Health and State of Charge Estimation Methods for Batteries Used in Electric Vehicle Applications,” MDPI World Elect. Veh. J., 2023.
Publication Date
5/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...