Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research
Abstract
:1. Introduction
1.1. Current Research Status
1.2. Motivation and Original Contribution
1.3. Configuration of This Paper
2. Experimental Section
3. Preliminary Analysis of Acoustic Signals
4. Results and Discussion for Acoustic Characteristics of Battery under Different Discharge Currents
4.1. Analysis of Acoustic Signal Characteristics in the Time Domain
4.2. Analysis of Acoustic Signal Characteristics in the Frequency Domain
5. Conclusions and Future Prospects
- Sensitivity to Discharge Conditions: The acoustic signals displayed pronounced differences in behavior under low (0.5 C) and high (3 C) discharge conditions. Specifically, lower discharge rates showed more stable acoustic signals, indicating lesser structural impact, whereas higher rates exhibited significant reductions in center frequency amplitude and the emergence of multi-peak phenomena, signaling substantial internal structural stress.
- Diagnostic Accuracy: the delay in acoustic signal change (Δt1) under 3 C discharge was found to be four times greater, on average, compared to 0.5 C, indicating heightened sensitivity to higher discharge rates. The amplitude of the acoustic signals (ΔAE) showed an average of 1.35 times greater variation under 3 C than under 0.5 C, suggesting a more significant impact on the battery’s internal structure at higher discharge rates. The duration of the acoustic signals (Δt2) extended by an average of 1.3 times under 3 C conditions, reflecting the more substantial structural changes and stress experienced by the battery.
- Implications for Battery Management: The discharge current of electric vehicles fluctuates within a certain range, depending on operating conditions. Under conditions where temperature variations are not considered, it is generally believed that higher current charging and discharging put greater stress on the battery structure, causing more significant structural damage, thus generating more pronounced acoustic signals. Therefore, one important purpose of acoustic monitoring is to promptly capture the acoustic characteristics associated with significant structural damage induced by 3 C high currents; on the other hand, capturing acoustic signals at 0.5 C low currents helps monitor long-term changes in battery structure, which is very helpful for understanding battery aging.
- Future Prospects: Building on the current findings, future research will focus on refining the integration of acoustic diagnostics within BMS. This includes enhancing the precision of fault detection and increasing the reliability of the diagnostics through advanced signal processing techniques and the integration of machine learning algorithms. Additionally, exploring the scalability of this technology for different battery types and operational conditions in EVs will be crucial. The research will also delve into the development of real-time adaptive monitoring strategies that can dynamically adjust to changing battery conditions, thereby optimizing battery performance and extending lifespan. The ultimate goal is to utilize acoustic diagnostics not only for safety and maintenance but also for the proactive management of battery health, thereby supporting the broader application of EVs in sustainable transportation.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
EVs | electric vehicles |
SOC | state of charge |
BMS | battery management system |
SA | signal amplitude |
LIBs | lithium-ion batteries |
TOF | time of flight |
FIR | Finite Impulse Response |
UT | ultrasonic testing |
AE | acoustic emission |
SEI | solid electrolyte interface |
NDT | non-destructive testing |
FFT | Fast Fourier Transform |
CAN | controller area network |
NMC | nickel manganese cobalt oxide |
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Type of Battery Cell | 18650-Type Cylindrical NMC Lithium Cells |
---|---|
Nominal cell capacity (0.3 C) | 2.0 Ah |
Average battery cell voltage | 3.6 V |
End of discharge voltage | 2.5 V |
High voltage protection | 4.2 V |
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Zhou, N.; Wang, K.; Shi, X.; Chen, Z. Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research. World Electr. Veh. J. 2024, 15, 229. https://doi.org/10.3390/wevj15060229
Zhou N, Wang K, Shi X, Chen Z. Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research. World Electric Vehicle Journal. 2024; 15(6):229. https://doi.org/10.3390/wevj15060229
Chicago/Turabian StyleZhou, Nan, Kunbai Wang, Xiang Shi, and Zeyu Chen. 2024. "Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research" World Electric Vehicle Journal 15, no. 6: 229. https://doi.org/10.3390/wevj15060229