Active Acoustic Emission Sensing for Fast Co-estimation of State of Charge and State of Health of the Lithium-ion Battery

Zuolu Wang, Xiaoyu Zhao, Hao Zhang, Dong Zhen, Fengshou Gu, Andrew Ball

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

With the rapid development of clean energy technologies, the lithium-ion batteries have emerged as dominant power source. It is of great significance to monitor the state of charge (SOC) and state of health (SOH) accurately and efficiently for ensuing high safety and reliability. This paper proposes an active acoustic emission (AE) sensing technology and demonstrates the feasibility for coestimation of SOC and SOH of the lithium-ion battery. The proposed method aims to achieve a fast monitoring of SOC and SOH by putting insights into the variation of material properties during operations. In the method, the appropriate power ultrasound is used to excite the battery and trigger elastic waves. A wide AE transducer can actively capture the released AE events of the battery material with different properties in a wide range of frequency band. Therefore, this allows the battery SOC/SOH to be fast characterised during charging, discharging, and ageing. Experimental studies have found that calculated RMS of AE signals in the frequency band 270-300 kHz, around the 7th harmonic of ultrasonic excitation, can successfully achieve the joint estimation of battery SOC and SOH at any operating phases. This new finding can be designed as a standalone method for fast SOC/SOH estimation.
Original languageEnglish
Article number107192
Number of pages13
JournalJournal of Energy Storage
Volume64
Early online date23 Mar 2023
DOIs
Publication statusPublished - 1 Aug 2023

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