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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65140

Predictive twin technology battery management system

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65140

Volume:

10 |

6 |

Jun 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65140

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.

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Authors

CJ

Chinmay Jagadale

Electronics and Telecommuniication

Zeal Collage of Engineering and Research, Narhe, Pune, India

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KP

Kunal Patil

Electronics and Telecommuniication

Zeal Collage of Engineering and Research, Narhe, Pune, India

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VW

Vaishnavi Waghmode

Electronics and Telecommuniication

Zeal Collage of Engineering and Research, Narhe, Pune, India

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PM

Prajwal More

Electronics and Telecommuniication

Zeal Collage of Engineering and Research, Narhe, Pune, India

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Mentors

PVN

Prof. V. N.Mane

Electronics and Telecommuniication

Zeal Collage of Engineering and Research, Narhe, Pune, India

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Abstract

Electric vehicles are the way of the future. The rising EV market, along with the diminishing supply of petroleum fuels, demands the development of more efficient EVs. A battery management system (BMS) is an essential component of any electric vehicle. It consists of a number of electrical and electronic circuits (including converter and inverter circuits) that have been programmed to monitor and extract the maximum output from a battery system. The chemical reactions are what determine the battery’s performance. The performance of a battery degrades as chemicals decay. As a result, these features of a battery must be regularly monitored. Because of their high charge density and lightweight, Lithium-ion batteries have proven to be a popular choice among electric vehicle producers. Despite the fact that these batteries have a lot of power for their size, they are quite unstable. It is critical that these batteries are never overcharged or discharged, requiring the use of voltage and current regulators.In this research paper, we will monitor various aspects of the vehicles like current, Voltage, SOC and temperature with the help of Node MCU which is the Wi-fi enabled microchip that willsend the data or crucial parameters to the server which is the ThingSpeak. Therefore in this way we can monitor these parameters from anywhere and also monitor battery health.

KEYWORDS

IOT BMS Battery management Vehicle Battery system SOH insert

Cite This Article

Chinmay Jagadale, Kunal Patil, Vaishnavi Waghmode, Prajwal More, Prof. V. N.Mane, "Predictive twin technology battery management system," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-4, Jun 2026. https://doi.org/10.55041/IJSREM65140

Full Article/Conclusion

The proposed system is useful in monitoring and tracking the properties of the battery in real time. The battery plays a vital role in an Electric vehicle .Therefore monitoring of the Battery is very important. The project proposed a new way monitoringthe battery with the help IOT. The sensors incorporated in the proposed system can collect the data of battery such as voltage, temperature and current, these data is then sent to Arduino IOT Cloud . Thus the real time data collection, storage and monitoring of the battery of an electric vehicle is possible with the system. By tracking these variables, it will be easier to determine the battery’s health or longevity, and pricing will be adjusted accordingly, as a less efficient battery with a shorter life cycle will cost more than a more efficient battery with a longer life cycle. This helps in identifying and solving a problem before a failure without human dependency. In addition measured data helps to develop a battery swapping station and its price fixing.

References

[1]     Rajashekara, K., 2013. Present status and future trends in electric vehicle propulsion technologies. IEEE journal of emerging and selected topics in power electronics, 1(1), pp.3-10. [2]     Denton, T., 2020. Electric and hybrid vehicles. Routledge. [3]     Zhang, F., 2017. Modeling and control of a modular battery management system for lithium-ion battery packs (Doctoral dissertation, University of Colorado at Boulder). [4]     Hemmati, M., Abapour, M. and Mohammadi-Ivatloo, B., 2020. Optimal scheduling of smart Microgrid in presence of battery swapping station of electrical vehicles. In Electric Vehicles in Energy Systems (pp. 249-267). Springer, Cham. [5]     Shah, F.A., Sheikh, S.S., Mir, U.I. and Athar, S.O., 2019, August. Battery health monitoring for commercialized electric vehicle batteries: Lithium-ion. In 2019 International Conference on Power  Generation Systems and Renewable Energy Technologies (PGSRET) (pp. 1-6). IEEE. [6]     S. Jain, Z. Ahmad, M. S. Alam and Y. Rafat, "Battery Swapping Technology," 2020 5th IEEE International Conference on Recent Advances and Innovations in  Engineering(ICRAIE), 2020, [7]     Maitreya, S., Jain, H. and Paliwal, P., 2021, February. Scalable and Decentralized Battery Management System for Parallel Operation of Multiple Battery Packs. In 2021 Innovations in Energy Management and RenewableResources (52042) (pp. 1-7). IEEE. [8]     Ananthraj, C.R. and Ghosh, A., 2021, January. Battery Management System in Electric Vehicle. In 2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-6). IEEE. [9]     Kur’s, Andre; Moffatt, Robert; Solace, Marin, "Simultaneous midrange power transfer to multiple devices," Applied Physics Letters, vol.96, no.4, pp.044102, 044102-3, Jan  

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Publication Date

6/17/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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