EV BMS WITH CHARGE MONITOR AND FIRE PROTECTION
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Abstract
Battery storage forms the most important part of any electric vehicle (EV) as it stores the necessary energy for the operation of EV.So, in order to extract the maximum o/p of a battery & to ensure its safe operations it is necessary that a efficient battery management system exist is the same .It monitors the Parameters, determine SOC and provide necessary services to ensure safe operation of battery. Hence BMS forms a integral part of any EV and safe guards both the user and the battery by ensuring that the cell operates within its safe operating parameters. The proposed system only monitor the battery and charge it safely but also protect it to avoid accidents from occurring. The proposed model has following functions current, voltage measurement, state of charge (SOC) calculation, protection, battery status detection, liquid crystal display (LCD) etc. Electric vehicles (EVs) are automobiles powered by one or more electric motors, which draw energy from rechargeable batteries instead of relying solely on internal combustion engines (ICEs) that consume fossil fuels. A Battery Management System (BMS) is a critical component in electric vehicles (EVs) and other battery-powered systems. It monitors and controls the operation of the battery pack, ensuring its optimal performance, safety, and longevity. State of Charge (SoC) refers to the measure of the remaining energy in a battery, expressed as a percentage of its total capacity. It indicates how much charge is available in the battery at a given time, allowing users to estimate the remaining range or usage time before recharging is required.
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References
Y. Liu, X. Qian, and H. Guan, "Development of electric vehicle battery management system with charge
balance control," IEEE Transactions on Power Electronics, vol. 28, no. 6, pp. 2901-2908, Jun. 2013.
D. Chao, C. Shen, and K. S. Low, "Real-time state-of-charge estimation for electric vehicle batteries using a
coupled electrochemical-thermal model," Journal of Power Sources, vol. 329, pp. 261-268, Jan. 2017.
J. Li, J. Fan, and J. Li, "A novel active cell balancing scheme for series-connected battery packs of electric
vehicles," IEEE Transactions on Vehicular Technology, vol. 68, no. 5, pp. 4138-4148, May 2019.
D. Wang, Z. Xu, and L. Xu, "An integrated thermal management system for lithium-ion battery pack in electric
vehicles," Journal of Power Sources, vol. 329, pp. 337-348, Jan. 2017.
H. Guo, M. H. Ang, and Y. Cheng, "Development of a fire detection system for lithium-ion battery in electric
vehicles," Journal of Power Sources, vol. 325, pp. 405-412, Nov. 2016.
W. Cheng, X. Luo, and B. Yang, "Online fault diagnosis for lithium-ion batteries in electric vehicles using
neural network ensemble," IEEE Transactions on Industrial Informatics, vol. 14, no. 4, pp. 1735-1744, Apr.