A Connectivity-Based Outlier Factor Method for Rapid Battery Internal Short-Circuit Diagnosis
Abstract
:1. Introduction
- (1)
- A COF-based ISC fault diagnosis method is proposed, effectively amplifying the abnormal data in the voltage signal and improving the ability to diagnose early ISC faults.
- (2)
- The voltage sequence is processed to enhance fault characteristics, minimize the effects of voltage fluctuations during battery discharge, and accelerate the fault diagnosis process.
- (3)
- An ISC fault experiment is conducted under urban-dynamometer driving schedule (UDDS) working conditions to verify the effectiveness of the proposed method under different fault severities and varying conditions.
2. Methodology
2.1. Connectivity-Based Outlier Factor Algorithm
2.2. Fault Diagnosis Scheme
2.2.1. Feature Extraction
2.2.2. Fault Diagnosis
3. Design of Experiment
4. Results and Discussion
4.1. Fault Experiment Data Results and Processing
4.2. Fault Diagnosis Results
4.3. Comparison with Autoencoder-Based Methods
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
Li-ion | Lithium-ion |
ISC | Internal short-circuit |
MDM | Mean difference model |
SOC | State of charge |
COF | Connectivity-based outlier factor |
UDDS | Urban dynamometer driving schedule |
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Method Type | ||
---|---|---|
Model-Based Approach | Data-Driven Approach | Proposed Method |
Relies on accurate battery modeling, which is complex and susceptible to noise and actual operating conditions. | Poses difficulties in accurately identifying early ISC features and is easily affected by noise | Does not require building complex models, strong early ISC identification capabilities. |
Battery Type | Nominal Voltage (V) | Nominal Capacity (Ah) | Charge Cutoff Voltage (V) | Discharge Cutoff Voltage (V) |
---|---|---|---|---|
INR18650-2P | 3.7 | 2000 | 4.2 | 2.5 |
Experiment Number | Fault Type | Fault Parameters | Start Time |
---|---|---|---|
01 | No fault status | None | 0 s |
02 | ISC fault | 1 Ω | 600 s |
03 | ISC fault | 5 Ω | 600 s |
04 | ISC fault | 10 Ω | 600 s |
05 | ISC fault | 50 Ω | 600 s |
06 | ISC fault | 100 Ω | 600 s |
Fault Trigger Time | Diagnosis Time (s) | ||||
---|---|---|---|---|---|
1 Ω | 5 Ω | 10 Ω | 50 Ω | 100 Ω | |
600 s | 604 s | 619 s | 629 s | 723 s | 807 s |
Method | Fault Trigger Time | Diagnosis Time (s) | |
---|---|---|---|
1 Ω | 50 Ω | ||
Proposed method | 600 s | 604 s | 723 s |
Autoencoder | 600 s | 612 s | 8340 s |
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Dong, Z.; Li, G.; Xie, F.; Zhao, S.; Ji, X.; Tian, M.; Liu, K. A Connectivity-Based Outlier Factor Method for Rapid Battery Internal Short-Circuit Diagnosis. Sustainability 2025, 17, 5147. https://doi.org/10.3390/su17115147
Dong Z, Li G, Xie F, Zhao S, Ji X, Tian M, Liu K. A Connectivity-Based Outlier Factor Method for Rapid Battery Internal Short-Circuit Diagnosis. Sustainability. 2025; 17(11):5147. https://doi.org/10.3390/su17115147
Chicago/Turabian StyleDong, Zhiguo, Gongqiang Li, Fengxiang Xie, Shiwen Zhao, Xiaofan Ji, Mofan Tian, and Kailong Liu. 2025. "A Connectivity-Based Outlier Factor Method for Rapid Battery Internal Short-Circuit Diagnosis" Sustainability 17, no. 11: 5147. https://doi.org/10.3390/su17115147
APA StyleDong, Z., Li, G., Xie, F., Zhao, S., Ji, X., Tian, M., & Liu, K. (2025). A Connectivity-Based Outlier Factor Method for Rapid Battery Internal Short-Circuit Diagnosis. Sustainability, 17(11), 5147. https://doi.org/10.3390/su17115147