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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM56886

Battery Degradation Prediction and Life Estimation

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM56886

Volume:

10 |

2 |

Feb 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM56886

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

KPP

Kshitija P. Pathak

AKK

Aishwarya K. Kotkar

SYH

Shravani Y. Hengade

NRW

Nidhi R. Warungase

PJS

P. J. Suslade

DKL

D. K. Lakhe

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Abstract

With more devices depending on batteries, there’s a growing need to check their performance and ensure they stay safe. Over time, batteries can degrade because of things like heat, high electricity use, and frequent charging and discharging. This can make them less effective and even dangerous. This project introduces a system that helps predict how much a battery will wear out and how long it will still work. The system keeps track of voltage, current, and temperature to determine how much charge is left (SOC) and how healthy the battery is (SOH). It can spot problems early and guess how well the battery will perform in the future, which helps it last longer and work more reliably. It also has a feature that detects sparks, which improves safety by turning on a cooling fan when the battery gets too hot. The system uses a small computer chip to provide up-to-date information about the battery’s condition. It’s an affordable and dependable solution that can be used in many places where batteries are important.

KEYWORDS

Battery Degradation State of Charge (SOC) State of Health (SOH) Battery Monitoring System Spark Detection Cooling Fan Safety Mechanism Real-Time Monitoring Embedded System.

Cite This Article

Kshitija P. Pathak, Aishwarya K. Kotkar, Shravani Y. Hengade, Nidhi R. Warungase, P. J. Suslade, D. K. Lakhe, "Battery Degradation Prediction and Life Estimation," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 2, Feb 2026. https://doi.org/10.55041/IJSREM56886

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Publication Date

2/24/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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