A new collaboration between Dynexus Technology, Inc. and Pattern Computer, Inc., a company that uses pattern recognition to make complex datasets understandable and actionable, is giving Inline Rapid Impedance Spectroscopy (iRIS) technology a boost of artificial intelligence (AI).
In 2011, Idaho National Laboratory researchers developed a technology for measuring battery health and safety.
By sending multiple waves of electrical current simultaneously through a battery, iRIS determines the battery’s resistance and can monitor how the resistance changes over time. This data can inform about the battery’s state of charge, health, and safety. Dynexus exclusively licensed the iRIS technology from Idaho National Laboratory in 2015.
Even without AI, iRIS improves upon other, similar battery diagnostic tools. Due to its efficiency, iRIS can generate a wealth of data within seconds while simultaneously taking measurements as the battery is charging or discharging. iRIS can also measure up to 50 volts, although Dynexus researchers are currently working on a version that can measure up to at least 100 volts, which can be used for various battery module configurations.
By combining iRIS with Pattern Computer’s Pattern Discovery Engine, researchers hope to make the tool even more powerful.
“In order for the reuse and remanufacture of batteries to be sustainable, we need to be able to finance and insure second-use battery assets,” said David Sorum, CEO of Dynexus Technology, Inc. “We need to understand the remaining capacity and state of health throughout a battery’s lifecycle. Working together, Dynexus and Pattern can significantly help solve that challenge.”
Battery integrators could use the hybrid iRIS/Pattern technology for difficult diagnostic challenges, such as predicting battery failures or matching similar batteries together within the same device so they deliver optimal performance.
Tanvir Tanim, a senior battery research and development scientist at INL, uses iRIS during his research and benchmarks the technology against other diagnostic tools.
“It is one of the diagnostics that may be useful to understand battery performance, life, and safety early on,” said Tanim. “If you just look at conventional measurements, such as voltage, temperature and current, it is often difficult to accurately measure a battery’s state of health and state of safety.”
“The Dynexus-Pattern collaboration is one example of how a technology developed and tested at INL, and commercialization by private companies could potentially have a big impact on industry,” said INL commercialization manager Ryan Bills. “With iRIS, Dynexus has attracted interest from customers in industry and government. Now, the Pattern partnership forms the basis for something new. Together, they are going to improve how battery health is measured, moving the needle from battery diagnostics to battery prognostics to help maximize battery value and improve safety.”
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