SBIR/STTR Award attributes
NASA seeks intelligent monitoring and prognostic for hybrid and/or all-electric propulsion systems. nbsp;A key component of these systems is the energy storage sub-system in which Lithium-ion batteries occupy a prominent place. We propose a novel, accurate and cost-effective Multi-Domain Sensing System for Lithium-ion batteries capable of detecting thermal runways earlier and predicting Remaining Useful Life (RUL) more accurately than existing methods. This technology has the capability to detect incipient faults inside Lithium-ion cells in their early stages. This will enable the effective deployment of modern protection mechanisms that are proactive and act to isolate faults with sufficient time before catastrophic effects are detected. This capability is further exploited in our system to tackle the important problem of predicting the RUL of a Lithium-ion battery in a way that promises higher levels of accuracy. All this is accomplished within an Artificial Intelligence and Stochastic-based framework that will take Lithium-ion battery monitoring and prognostics to the next level. The early detection of faults combined with the more accurate prediction of their RUL will ensure lives and assets are protected while improving the operational and ownership cost of energy storage systems based on current or future Lithium-ion batteries.
