Karmactive Team
MIT researchers have discovered that batteries make specific sounds as they degrade, potentially offering a simple way to monitor battery health and prevent failures before they happen.
The research team found that by carefully analyzing the faint noises coming from lithium-ion batteries, they could identify whether the battery was experiencing gas bubbles forming or materials cracking inside – two major causes of battery failure.
“In this study, through some careful scientific work, our team has managed to decode the acoustic emissions,” said Martin Z. Bazant, professor of chemical engineering and mathematics at MIT and co-author of the study published in the journal Joule on September 5.
Unlike current expensive testing methods, this approach is completely non-destructive and passive. The batteries continue operating normally while being monitored.
“I think the core of this work is to look at a way to investigate internal battery mechanisms while they’re still charging and discharging, and to do this nondestructively,” explained Yash Samantaray, an MIT graduate student and author of the study.
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The breakthrough came when researchers paired sound recordings with electrical measurements during regular battery charging and discharging. This combination helped them connect specific sounds to what was physically happening inside.
“We were able to classify them as coming from gas bubbles that are generated by side reactions, or by fractures from the expansion and contraction of the active material, and to find signatures of those signals even in noisy data,” Bazant explained.
Traditional methods simply record when overall sound levels exceed a certain threshold. The MIT team went further by tracking voltage and current alongside sound characteristics. “We know that emissions happen at a certain potential [voltage], and that helps us identify what the process might be that is causing that emission,” Bazant said.
The team used a technique called wavelet transform – essentially a way to analyze both the frequency and duration of sounds – to create distinct “signatures” that stand out from background noise. After testing, they opened the batteries and examined them under electron microscopes to confirm their findings.
This discovery could benefit electric vehicles and grid-scale battery installations. For electric car owners, a sound monitoring system could provide advance warning before battery failures, potentially preventing dangerous thermal runaway that leads to battery fires.
Bazant compared the early detection capability to “seeing the first tiny bubbles in a pot of heated water, long before it boils.” In related work with Oak Ridge National Laboratory, the team has already shown that acoustic emissions can provide early warning of thermal runaway conditions.
Manufacturers could also use this technique during production to improve quality control. When batteries are first made, they go through a “formation cycling” process of charging and discharging that prepares them for use. Sound monitoring could quickly identify poorly formed cells early in this process, saving time and reducing waste.
“The most expensive and rate-limiting process in battery production is often the formation cycling,” Bazant noted. Sound monitoring could help “isolate well-formed cells from poorly formed cells very early, even before the useful life of the battery, when it’s being made.”
The team is already working to turn this discovery into practical applications. They have received a grant from Tata Motors to develop a battery monitoring system for electric vehicles. Samantaray also suggested it could become “a lab tool for groups that are trying to develop new materials or test new environments” without having to destroy test batteries.
The research was supported by the Toyota Research Institute, the Center for Battery Sustainability, the National Science Foundation, and the Department of Defense, with testing facilities provided by MIT.nano. This technology could lead to longer-lasting power for various applications in the future.
