Lithium Battery Early Warning Fault Indication System

Enhanced battery failure detection accuracy and reliability involves the integration of novel sensors and algorithms that are able to extract relevant information from the cells in a battery pack. This must be accomplished with minimum cost of ownership, installation, and operation. X-wave Innovations Inc. (XII), and its partners, The University of Maryland and The Boeing Company, propose to tackle this problem in a two tier approach. First, we will perform an analysis of the failure mechanisms to demonstrate the response of failed cells. We will be using our existing data, and will perform tests when necessary, taking into account multiple chemistries, the application profiles, the suite of targeted sensors, and the environment. This effort will result in the enhancement of our current data fusion algorithms, which will be tuned to the specific Navy application. Based on the previous efforts, our second step will be to develop a novel low cost SWaP embedded system that combines conventional sensors with a low-cost and low-power set of unique transducers capable of detecting battery faults reliably. By the end of Phase I our system will provide an accurate representation of the battery's safety state with technology that will require minimum installation and commissioning effort.