Fast and Smart State Characterization of Large-Format Lithium-Ion Batteries via Phased-Array Ultrasonic Sensing...

Area of Science:

• Materials Science
• Electrical Engineering
• Non-destructive Testing

Background:

• Lithium-ion batteries (LIBs) are critical for electric vehicles and energy storage, necessitating precise state monitoring.
• Current methods for LIB state characterization face limitations in accuracy and real-time monitoring capabilities.
• Accurate monitoring of battery states, including state of charge (SOC) and internal conditions, is vital for safety and performance.

Purpose of the Study:

• To develop and validate a novel characterization method for large-format LIBs using phased-array ultrasonic technology (PAUT).
• To establish a correlation between ultrasonic signals, phased array images, and battery states (SOC, gas generation).
• To provide a non-destructive and accurate approach for real-time LIB state monitoring.

Main Methods:

• Development of a finite element model simulating ultrasonic wave propagation in a multilayer porous medium for a large-format LIB.
• Conducting phased array ultrasonic imaging under various operating conditions, including abnormal gas generation.
• Experimental testing of a 40 Ah ternary lithium battery (NCMB) at a 0.5C charge-discharge rate to extract ultrasonic data and SOC.
• Designing and training a fully connected neural network (FCNN) model for SOC estimation.

Main Results:

• A strong relationship was established between ultrasonic signals, phased array images, and battery states through simulation and experimental validation.
• The FCNN model achieved a state of charge (SOC) estimation error of less than 4%.
• Phased array imaging detected gas bubble formation starting at 0.9 V and increasing significantly at 0.2 V during overcharging/overdischarging.

Conclusions:

• Phased-array ultrasonic technology (PAUT) offers a promising new method for accurate, non-destructive characterization of large-format lithium-ion batteries.
• The developed method enables reliable state of charge (SOC) estimation and early detection of critical internal changes like gas generation.
• This research contributes a valuable tool for enhancing the safety and operational efficiency of LIBs in demanding applications.