Authors :
Dr. Archana Shirbhate; Mohd. Aasim Ameen; Mohd. Irshadalam; Ritik Satpute
Volume/Issue :
Volume 10 - 2025, Issue 4 - April
Google Scholar :
https://tinyurl.com/mzhvnkjk
Scribd :
https://tinyurl.com/3zfuaxmd
DOI :
https://doi.org/10.38124/ijisrt/25apr157
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Abstract :
In this paper, a Battery Management System (BMS) is developed using the ESP32 micro-controller integrated
with voltage and current sensors to enhance the efficiency and lifespan of batteries in electric vehicles (EV). The primary
objective is to continuously monitor key parameters such as voltage, current, State of Charge (SoC) and State of Health
(SoH) to ensure optimal performance and safety. Pulse Width Modulation (PWM) techniques are employed to precisely
regulate the charging and discharging processes, reducing energy losses and preventing battery degradation. The ESP32
micro-controller is known for its low power consumption and built-in Wi-Fi and Bluetooth capabilities, acts as the central
processing unit, collecting real-time data and transmitting it to a cloud-based platform or local server for further analysis.
Advanced algorithms and cell balancing techniques are integrated to provide accurate SoC and SoH estimation, ensuring
uniform charge distribution across cells. Additionally, the BMS includes protection mechanisms against over-voltage,
under-voltage and over-current conditions, enhancing safety and reliability.The proposed system offers a cost-effective
and reliable solution for battery management in EV, focusing on efficient energy utilization, safety and extended battery
life.
References :
- A Tashakori and M. Ektesabi, "Stability analysis of sensorless BLDC motor drive using digital PWM technique for electric vehicles," IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, Montreal, QC, Canada, 2012, pp. 4898-4903, doi: 10.1109/IECON.2012.6388991
- B K. Lee and M. Ehsani, "Advanced BLDC motor drive for low cost and high performance propulsion system in electric and hybrid vehicles," IEMDC 2001. IEEE International Electric Machines and Drives Conference (Cat. No.01EX485), Cambridge, MA, USA, 2001, pp. 246-251, doi: 10.1109/IEMDC.2001.939307.
- A Sathyan, N. Milivojevic, Y. -J. Lee, M. Krishnamurthy and A. Emadi, "An FPGA-Based Novel Digital PWM Control Scheme for BLDC Motor Drives," in IEEE Transactions on Industrial Electronics, vol. 56, no. 8, pp. 3040-3049, Aug. 2009, doi: 10.1109/TIE.2009.2022067.
- N Milivojevic, M. Krishnamurthy, Y. Gurkaynak, A. Sathyan, Y. -J. Lee and A. Emadi, "Stability Analysis of FPGA-Based Control of Brushless DC Motors and Generators Using Digital PWM Technique," in IEEE Transactions on Industrial Electronics, vol. 59, no. 1, pp. 343-351, Jan. 2012, doi: 10.1109/TIE.2011.2146220.
- José Carlos Gamazo-Real,Ernesto Vázquez-Sánchez andJaime Gómez-Gil,:Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends, Sensors, 2010, Vol. 10, No. 6901, MDPI : https://www.mdpi.com/1424-8220/10/7/6901
- A. Tashakori , M. Ektesabi , N. Hosseinzadeh,:Characteristics of Suitable Drive Train for Electric Vehicle,119, 2011, Doi:https://doi.org/10.1115/1.859902.paper119
- P Damodharan and K. Vasudevan, "Sensorless Brushless DC Motor Drive Based on the Zero-Crossing Detection of Back Electromotive Force (EMF) From the Line Voltage Difference," in IEEE Transactions on Energy Conversion, vol. 25, no. 3, pp. 661-668, Sept. 2010, doi: 10.1109/TEC.2010.2041781.
- Jianwen Shao, D. Nolan and T. Hopkins, "A novel direct back EMF detection for sensorless brushless DC (BLDC) motor drives," APEC. Seventeenth Annual IEEE Applied Power Electronics Conference and Exposition (Cat. No.02CH37335), Dallas, TX, USA, 2002, pp. 33-37 vol.1, doi: 10.1109/APEC.2002.989224.
- Tae-Hyung Kim and M. Ehsani, "Sensorless control of the BLDC motors from near-zero to high speeds," in IEEE Transactions on Power Electronics, vol. 19, no. 6, pp. 1635-1645, Nov. 2004, doi: 10.1109/TPEL.2004.836625.
- T Kim, Chungil Kim and J. Lyou, "A new sensorless drive scheme for a BLDC motor based on the terminal voltage difference," IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society, Melbourne, VIC, Australia, 2011, pp. 1710-1715, doi: 10.1109/IECON.2011.6119564.
- Gui-Jia Su and J. W. McKeever, "Low cost sensorless control of brushless DC motors with improved speed range," APEC. Seventeenth Annual IEEE Applied Power Electronics Conference and Exposition (Cat. No.02CH37335), Dallas, TX, USA, 2002, pp. 286-292 vol.1, doi: 10.1109/APEC.2002.989260
- Y S. Lai and Y. -K. Lin, "Novel Back-EMF Detection Technique of Brushless DC Motor Drives for Wide Range Control Without Using Current and Position Sensors," in IEEE Transactions on Power Electronics, vol. 23, no. 2, pp. 934-940, March 2008, doi: 10.1109/TPEL.2007.915048.
- K Iizuka, H. Uzuhashi, M. Kano, T. Endo and K. Mohri, "Microcomputer Control for Sensorless Brushless Motor," in IEEE Transactions on Industry Applications, vol. IA-21, no. 3, pp. 595-601, May 1985, doi: 10.1109/TIA.1985.349715.
In this paper, a Battery Management System (BMS) is developed using the ESP32 micro-controller integrated
with voltage and current sensors to enhance the efficiency and lifespan of batteries in electric vehicles (EV). The primary
objective is to continuously monitor key parameters such as voltage, current, State of Charge (SoC) and State of Health
(SoH) to ensure optimal performance and safety. Pulse Width Modulation (PWM) techniques are employed to precisely
regulate the charging and discharging processes, reducing energy losses and preventing battery degradation. The ESP32
micro-controller is known for its low power consumption and built-in Wi-Fi and Bluetooth capabilities, acts as the central
processing unit, collecting real-time data and transmitting it to a cloud-based platform or local server for further analysis.
Advanced algorithms and cell balancing techniques are integrated to provide accurate SoC and SoH estimation, ensuring
uniform charge distribution across cells. Additionally, the BMS includes protection mechanisms against over-voltage,
under-voltage and over-current conditions, enhancing safety and reliability.The proposed system offers a cost-effective
and reliable solution for battery management in EV, focusing on efficient energy utilization, safety and extended battery
life.