基于超声波检测的锂离子电池荷电状态估计,Journal of Energy Storage

为了从锂电池内部材料特性表征锂电池的荷电状态，本文提出了一种基于超声波无损检测的锂电池荷电状态估算方法。本文首先利用超声波探伤仪等设备获取超声波检测反馈信号，然后引入经验模态分解（EMD）算法消除超声波反馈信号中存在的干扰，并将分解后的超声波反馈信号重构为提高超声波信号的连续性。其次，希尔伯特变换对超声波信号执行。以超声能量熵和超声接收熵为特征量，提取超声信号的最大瞬时能量来衡量锂电池的充电状态。最后，本文使用相关向量回归建立锂电池荷电状态估计模型。实验表明，本文提出的方法切实可行，具有较好的估计精度。本文提出的声学特性为后续的相关研究提供了一定的参考。

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In order to characterize the state of charge of the lithium battery from the internal material properties of the lithium battery, this paper proposes a method of estimating the state of charge of the lithium battery based on ultrasonic non-destructive testing. First, this paper uses the ultrasonic flaw detector and other equipment to obtain the feedback signal of ultrasonic detection, then introduces the empirical mode decomposition (EMD) algorithm to eliminate the interference present in the ultrasonic feedback signal, and reconstructs the decomposed ultrasonic feedback signal to improve the continuity of the ultrasonic signal. Secondly, the Hilbert transform is performed on the ultrasonic signal. The maximum instantaneous energy of the ultrasonic signal is extracted with the ultrasonic energy entropy and the ultrasonic reception entropy as the characteristic quantity to measure the charge state of the lithium battery. Finally, this paper uses relevance vector regression to build a lithium battery state of charge estimation model. The experiments show that the method proposed in the thesis is practical and feasible, and has good estimation accuracy. The acoustic characteristics proposed in this paper provide a certain reference for subsequent related research.