A Precise Minor-Fault Diagnosis Method for Lithium-Ion Batteries Based on Phase Plane Sample Entropy
Xin Gu, Jinglun Li, Kailong Liu, Yuhao Zhu, Xuewen Tao, Yunlong Shang
Abstract
Fault diagnosis technology can detect the minor anomalies of batteries, which is of crucial significance to ensuring the safe operation of electric vehicles (EVs). However, the voltages of early minor faults do not exceed the safety threshold, which is difficult to detect using the conventional fault diagnosis methods. Herein, a minor fault diagnosis approach for lithium-ion batteries based on phase plane sample entropy is presented. Specifically, the battery phase plane is defined for the first time, taking the voltages as abscissa and the first-order difference of voltages as ordinate. In addition, the two-dimensional sample entropy of each cell phase plane is calculated through a sliding window, which allows minor faults to be accurately detected and the time of occurrence of the fault to be predicted. The experimental results demonstrate the effectiveness, robustness, and generalizability of the proposed approach. More importantly, the presented technique achieves a 92.50% fault detection rate and an 82.33% detection accuracy rate with a minor fault amplitude of 50 mV, which are approximately 14% and 16% higher than that of the conventional sample entropy methods, respectively. In summary, the proposed method highlights the broad application of phase planes for battery fault diagnosis.