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https://at.inl.gov/SitePages/NextGenHighEnrgyBtry.aspxEnergy Storage Technology
  
https://at.inl.gov/SitePages/EnablingFastChrgBtry.aspxEnergy Storage Technology
  
https://at.inl.gov/sitePages/PhysicsBasedMachineLearn.aspxEnergy Storage Technology
  
https://at.inl.gov/SitePages/EnablingAdvncdD&P.aspxEnergy Storage Technology
  
https://at.inl.gov/SitePages/Advanced%20Electrolytes.aspxEnergy Storage Technology

​INL developed significant leadership in battery diagnosis, prognosis, and failure analysis. Notable techniques include quantitative electrochemical analyses, pressure-induced cell-performance improvements, fast diagnosis of failure mechanisms and lifetime prediction, and quantification of performance metrics to aid cell design and performance-improvement strategies using standardized testing protocols.

INL also extends some of these cell-level diagnostics to module and pack levels to identify imminent and long-term safety-critical issues and faults (e.g., battery hard shorts after a crash scenario) or nascent faults (e.g., battery soft shorts) that could potentilly develop into a safety-critical fault. Besides developing these diagnostic techniques, INL also works to advance the ability to systematically and more-directly compare the validity of different diagnostic tools for EV batteries. To facilitate the comparison, INL is developing a robust methodology and a reconfigurable, diagnostic evaluation platform capable of assessing different diagnostic tools and battery-management systems. The platform and methods will evaluate the real-time performance and stability in emerging safety-critical automotive situations—e.g., stranded energy, XFC, etc., for a host of different emerging diagnostic technologies. For more information please out the publications below.​

Publications



Research Contact:  Tanvir Tanim   -   Phone:  (208) 526-5713   -   Tanvir.Tanim@inl.gov

                                 ​  Eric Dufek   -   Phone:  (208) 526-2132   -   Eric.Dufek@inl.gov​