Online Nonintrusive Identification and Monitoring of Internal Weak Points of Electro Energy Devices Using Package Surface Temperature

University Of Nebraska-Lincoln, Lincoln NE

Investigators

Abstract

Electro-energy devices (such as batteries) play an essential role in modern society with their wide spread applications that span various sectors such as transportation, healthcare, communication and renewable energy generation to name a few. Currently, assessing the longevity of such devices while they are in operation is an extremely challenging task. As a result, there exists a huge risk of untimely failure of such devices in critical missions and/or situations leading to safety issues and financial loss. Currently, there are no general, effective approaches to online identification of internal weak points and monitoring of the aging processes and health conditions of different electro-energy devices while in operation. This project formulates and demonstrates new universal dynamic modeling and system identification methodologies for low-cost online identification and condition monitoring of internal weak points of electro energy devices using their package surface temperatures. The methodologies do not intrude upon the devices or interrupt their operation. The results of this research will enhance real-time, predictive condition awareness and improve the understanding of aging and failure mechanisms of electro energy devices, which will help in designing more reliable devices. Enhanced condition awareness and design will greatly improve safety and reliability and reduce the cost and financial risk of using electro energy devices. This project will provide interdisciplinary research training for graduate and undergraduate students and STEM education for K-12 school students focusing on dynamic system modeling and identification for energy systems applications. This project will create a new dynamic modeling and system identification-based universal mathematical framework for nonintrusive online identification and condition monitoring of internal weak points of electro energy devices using their thermal signature. The framework incorporates a new universal interpretation for the complex aging processes of internal weak points via the changes in the three-dimensional electrothermal dynamics of the devices estimated by measuring package surface temperatures. Based on this interpretation, a new mathematical modeling approach will be developed to adaptively characterize the aging-related electrothermal dynamics of the devices via high-fidelity, physics-based modeling, automated model order reduction with quantifiable error bounds, online parameter identification for the reduced-order model, and high-order model reconstruction. The identified parameters will contain information on locations, aging processes, and health conditions of the internal weak points and therefore can be used for condition monitoring of the electro energy devices. The framework will be validated by computer simulation and experimental studies to identify and monitor internal weak points of power semiconductor devices. In addition to electro energy devices, the research will provide enabling capabilities for modeling and diagnostics of other complex physical systems.