Researchers listen in as audible lithium battery anomalies reveal cracks and concealed malfunctions
Researchers at MIT have made a significant breakthrough in battery technology by developing a method to interpret acoustic signals produced by lithium-ion batteries during charging and discharging. This innovative approach, led by graduate student Yash Samantaray and Professor Martin Z. Bazant, along with Alexander Cohen, Daniel Cogswell, and others, was published on September 5 in the journal Joule.
The team's groundbreaking work allows for the investigation of internal battery mechanisms while they are still in operation, offering an additional 'window' beyond voltage and current in batteries. This method echoes how engineers track structural health in bridges, providing valuable insights into the health of lithium-ion batteries.
One immediate application of this research is in material research, where lab groups could potentially detect gas generation or particle fracturing without disassembling cells. Samantaray notes that this approach allows investigation without damaging cells, making it a non-invasive method for battery health monitoring.
In related work with Oak Ridge National Laboratory, the team demonstrated that acoustic data could warn of thermal runaway before it triggered fires. This finding underscores the potential of this method in ensuring the safety of lithium-ion batteries, particularly in electric vehicles and grid-scale systems.
The researchers coupled electrochemical testing with acoustic recordings under real-world conditions. By pairing voltage and current readings with sound patterns, they could pinpoint when certain emissions occurred, linking specific sound patterns to internal degradation processes like gas generation and fracturing of electrode materials.
The study received support from the Toyota Research Institute, the Center for Battery Sustainability, the National Science Foundation, and the Department of Defense. Bazant highlights the value in manufacturing, where early detection of faulty cells could cut costs during formation cycling. Furthermore, the method can reveal remaining useful life and even safety risks of batteries.
Notably, the group is already working with Tata Motors on a monitoring system for electric vehicles. However, no specific researchers were directly identified as currently working on developing acoustic signal-based methods to monitor the health of lithium-ion accumulators in electric vehicles and large-scale systems in the provided search results.
To separate distinct signals from background noise in battery acoustic signals, the MIT team used wavelet transforms. This low-cost method offers a promising solution for monitoring battery health in electric vehicles and grid-scale systems. By sensing issues early, it may be easier to isolate well-formed cells from poorly formed cells very early, even before the useful life of the battery.
In conclusion, the MIT team's decoding of acoustic emissions from lithium-ion batteries represents a significant step forward in battery health monitoring. This non-invasive, low-cost method offers potential benefits in various applications, from material research to electric vehicle manufacturing, and could contribute to safer and more efficient battery technology in the future.
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