Li-ion Battery Health Monitoring Using Vibration Analysis

Overview

Engineering, Worcester Polytechnic Institute, Worcester, MA With the growing demand for lithium -ion batteries (LIBs) in electric vehicles and energy storage, ensuring battery safety is critical. Conventional LIB monitoring relies on voltage, current, and temperature but is not capable of providing early warnings of battery abuses that make the LIBs more prone to thermal runaway. This study hypothesizes that vibration signals generated during LIB operations can distinguish different battery states. This study explores vibration-based health monitoring of LIBs. Sensors placed on the surface of LIB cells recorded vibration signals (0 –23 kHz) during normal operation and abusive conditions (overcharging/over-discharging). Fast Fourier Transform (FFT) and Gaussian smoothing were used to preprocess the data. Advanced data processing techniques, including cosine similarity and t-distributed stochastic neighbor embedding (t -SNE), were employed for data classification and assessing battery deviations from normal health conditions. When overcharged, LIB cells exhibited changes in vibration signals at key voltages, corresponding to different material structures at the cathode. Over -discharging revealed no significant vibration changes initially, but subsequent recharging showed distin ct stages in vibration signals, indicating potential alterations in electrode materials. Vibration signals from LIBs in healthy, previously over-discharged, and previously overcharged states showed three distinct clusters representing their health states. The distinguishable battery states observed through vibration measurements are consistent with previous X -ray diffraction studies reported in the literature. These findings demonstrate for the first time that vibration signals effectively detect subtle structural changes in LIBs, complementing conventional monitoring. This low -cost, nonintrusive approach provides early indicators of battery degradation, adding a new dimension to battery health diagnostics.

Competition history

• JSHS 2025 Category not listed

Resources

• National JSHS abstract book ↗

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