State estimation of a lithium-ion battery based on multi-feature indicators of ultrasonic guided waves

Li, Xiaoyü; Wen, Hao; Wu, Chuxin; Zheng, Shanpu; Tian, Yong; Tian, Jindong

doi:10.1016/j.est.2022.106113

Cited by 15 publications

(4 citation statements)

References 25 publications

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“…When guide waves on the incident to the cell, it introduces more aliasing and mode conversion after multiple layers, making the wave more complex and difficult to analyse. 28,29 In addition, guided wave measurements require a certain distance between transducers. This contains information about the entire measurement area, and it is not possible to distinguish localised ageing for small cell sizes.…”

Section: Methodsmentioning

confidence: 99%

“…In the characterisation of other types of batteries, the attenuation coefficient of acoustic waves has been used to represent lithium deposition. 28 It or its derived variables are often used to describe the decay process of elastic waves in other composites with periodic porous structures. [31][32][33][34] Thus, the acoustic attenuation coefficient of the longitudinal wave is used as a feature to characterise the capacity fading.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Ultrasonic Non-Destructive Testing on Fast-Charging Lithium-Ion Battery’s Capacity Fading

Sun,

Zhang,

Liu

et al. 2024

J. Electrochem. Soc.

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The ultrasonic inspection technique has been widely used for the internal structure detection and reaction process characterization of lithium-ion batteries because of its nondestructive testing properties. One of the main challenges in addressing the issue of charging time for power supplies with long-life requirements is fast charging, which is a crucial technological advancement. Fast charging, however, will shorten the charging period while also hastening the power battery’s capacity degradation, reducing its service life. This paper presents a method for monitoring the capacity attenuation of a fast-charging battery by calculating the ultrasonic attenuation coefficient. The experimental and calculation results show that the battery capacity decays nonlinearly with the increase in service time, which is a power function of the ultrasonic attenuation coefficient. Moreover, the inhomogeneous ageing of battery electrode material is detected and quantified based on the differences in acoustic signals, which provides new insights into battery health management and uneven ageing assessment.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Ultrasonic Non-Destructive Testing on Fast-Charging Lithium-Ion Battery’s Capacity Fading

Sun,

Zhang,

Liu

et al. 2024

J. Electrochem. Soc.

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show abstract

“…Common acoustic detection techniques include ultrasonic testing (UT) and AE research. UT is renowned for its proficiency in non-destructive testing (NDT), utilizing ultrasonic waves to inspect internal defects in diverse fields such as materials science, medicine, and structural engineering [6,7]. In the realm of battery technology, Sood et al [8] pioneered the adaptation of UT for LIBs, demonstrating its effectiveness in identifying structural changes that reflect the battery's health status.…”

Section: Current Research Statusmentioning

confidence: 99%

Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research

Zhou,

Wang,

Shi

et al. 2024

WEVJ

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The improvement of battery management systems (BMSs) requires the incorporation of advanced battery status detection technologies to facilitate early warnings of abnormal conditions. In this study, acoustic data from batteries under two discharge rates, 0.5 C and 3 C, were collected using a specially designed battery acoustic test system. By analyzing selected acoustic parameters in the time domain, the acoustic signals exhibited noticeable differences with the change in discharge current, highlighting the potential of acoustic signals for current anomaly detection. In the frequency domain analysis, distinct variations in the frequency domain parameters of the acoustic response signal were observed at different discharge currents. The identification of acoustic characteristic parameters demonstrates a robust capability to detect short-term high-current discharges, which reflects the sensitivity of the battery’s internal structure to varying operational stresses. Acoustic emission (AE) technology, coupled with electrode measurements, effectively tracks unusually high discharge currents. The acoustic signals show a clear correlation with discharge currents, indicating that selecting key acoustic parameters can reveal the battery structure’s response to high currents. This approach could serve as a crucial diagnostic tool for identifying battery abnormalities.

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“…The results showed that the average estimation error was 0.75%. Li et al [27] used a piezoelectric ceramic ultrasonic transducer to detect batteries by obtaining ultrasonic guided wave signals. Considering the frequency response of the transducer and the battery, the multi-frequency response characteristics of the battery were analyzed.…”

Section: Introductionmentioning

confidence: 99%

State of Charge and Temperature Joint Estimation Based on Ultrasonic Reflection Waves for Lithium-Ion Battery Applications

Zhang

Sun

et al. 2023

Batteries

Self Cite

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Accurate estimation of the state of charge (SOC) and temperature of batteries is essential to ensure the safety of energy storage systems. However, it is very difficult to obtain multiple states of the battery with fewer sensors. In this paper, a joint estimation method for a lithium iron phosphate battery’s SOC and temperature based on ultrasonic reflection waves is proposed. A piezoelectric transducer is affixed to the surface of the battery for ultrasonic–electric transduction. Ultrasonic signals are excited at the transducer, transmitted through the battery, and transmitted back to the transducer by reaching the underside of the battery. Feature indicator extraction intervals of the battery state are determined by sliding–window matching correlation analysis. Virtual samples are used to expand the data after feature extraction. Finally, a backpropagation (BP) neural network model is applied to the multistate joint estimation of a battery in a wide temperature range. According to the experimental results, the root mean square error (RMSE) of the lithium-ion battery’s SOC and temperature estimation results is 7.42% and 0.40 °C, respectively. The method is nondestructive and easy to apply in battery management systems. Combined with the detection of gas production inside the battery, this method can improve the safety of the battery system.

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State estimation of a lithium-ion battery based on multi-feature indicators of ultrasonic guided waves

Cited by 15 publications

References 25 publications

Ultrasonic Non-Destructive Testing on Fast-Charging Lithium-Ion Battery’s Capacity Fading

Ultrasonic Non-Destructive Testing on Fast-Charging Lithium-Ion Battery’s Capacity Fading

Detection and Analysis of Abnormal High-Current Discharge of Cylindrical Lithium-Ion Battery Based on Acoustic Characteristics Research

State of Charge and Temperature Joint Estimation Based on Ultrasonic Reflection Waves for Lithium-Ion Battery Applications

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