The Remaining Capacity Estimation of Li-Ion Battery Based on Regional Ultrasonic Energy Characteristic

• Published in: IEEE access Vol. 12; pp. 128541 - 128550
• Main Authors: Cai, Zhiduan, Jiang, Haoye, Xu, Lihao, Qin, Chenwei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Aging; Batteries; Contingency; Feature extraction; least squares; Least squares approximations; Least squares method; Lithium batteries; Lithium power battery; Lithium-ion batteries; Regional analysis; regional energy feature; remaining capacity; State of charge; ultrasonic detection; Ultrasonic imaging; Ultrasonic testing
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3457546

In recent years, the application of ultrasonic detection technology in the estimation of lithium battery performance states has achieved some results, such as remaining capacity. The remaining capacity is characterized by using ultrasonic feature quantities under a certain state of charge. Such methods to extract features can lead to a phenomenon that multiple ultrasonic signals may correspond to a single state of charge, increasing the contingency of feature extraction and reducing the accuracy of remaining capacity estimation. To this end, an ultrasonic regional energy characterization method is proposed in this paper to enhance the accuracy, and the correlation between ultrasonic regional energy feature quantity and remaining capacity is analyzed. Then the intervals and sampling points to select feature quantities are decided, and the least squares method is utilized to build the capacity degradation model, which can estimate remaining capacity. Finally, the feasibility and effectiveness of the proposed estimation method are verified through experiments.