Battery Condition Monitoring
Fast and precise assessment of battery health and performance conditions.Ability to achieving a more complete and accurate health metric.Support both battery diagnostics and prognostics with embedded predictive data analytics and learning.Adaptable to user needs and preferences for given applications.Amenable to include new and expanded electrochemical definitions for battery health.
Plug-in electric vehiclesPortable electronics, such as phones, laptops, and wearablesEnergy storage systems for:MicrogridsUtilitiesCell towersData centersUnmanned Aerial Systems (UAS)Battery infrastructures for energy and weapon systems
Researchers at IdahoNational Laboratory have developed a new advanced methodology for real-timebattery health analysis and performance optimization that utilizes embeddeddata analytics and machine learning techniques. The system combines active(e.g. impedance) with passive (e.g. temperature) measurements withcomputationally-efficient data analytics and machine learning to assess realtime health under load operation. The system is capable of estimating severalhealth and performance metrics including State-of-Charge (SOC), State-of-Health(SOH), and Remaining-Useful-Life (RUL). The capability supports the productionof smart battery products with sufficient intelligence to allow for automated,real-time control and optimization.
LICENSINGOPPORTUNITY: IdahoNational Laboratory (INL) and its M&O Contractor Battelle Energy Alliance,LLC (BEA) are currently looking for commercialization partner(s) interested inentering into a license agreement for the purpose of commercializing thetechnology described below. INTELLECTUALPROPERTY STATUS: This invention has associated intellectual property USPatent Application No. 15/357,322, BEA Docket No. BA-431: “Systems and Methodsfor Estimation and Prediction of Battery Health and Performance,” submitted 21November 2016. DEVELOPMENTSTATUS: This technology has been tested and validated at thebench scale. Additional development will be required to demonstrate a pilotscale process. ADDITIONALINFORMATION:
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