Acoustic Analysis for Battery Testing
In order to meet the safety and lifetime requirements for battery systems, battery makers are forced to impose both tight quality control limits on production and enact conservative operating limits for their batteries. These constraints are necessary because the current state of the art for battery monitoring – simple voltage, current, and temperature measurements – does not provide adequate information or certainty on what is going on inside the battery. With such limited information, conservative limits are the only way to reliably manage the battery’s internal chemistry and limit its susceptibility to adverse chemical reactions. There is an opportunity for innovation in sensing technologies that dramatically enhance battery diagnostics during operation, thus enabling dynamic, real-time battery health monitoring and management. New approaches to achieve higher fidelity, more robust, and lower cost sensing and control of battery packs are needed to improve overall battery safety and performance.
Project Innovation + Advantages:
Princeton University is developing a non-invasive, low-cost, ultrasonic diagnostic system to determine battery state-of-health and state-of-charge, and to monitor internal battery defects. This system links the propagation of sound waves through a battery to the material properties of components within the battery. As a battery is cycled, the density and mechanical properties of its electrodes change; as the battery ages, it experiences progressive formation and degradation of critical surface layers, mechanical degradation of electrodes, and consumption of electrolyte. All of these phenomena affect how the sound waves pass through the battery. There are very few sensing techniques available that can be used during battery production and operation which can quickly identify changes or faults within the battery as they occur. As an ARPA-E IDEAS project, this early stage research project will provide proof of concept for the sensing technique and build a database of acoustic signatures for different battery chemistries, form factors, and use conditions. If successful, this ultrasonic diagnostic system will improve battery quality, safety, and performance of electric vehicle and grid energy storage systems via two avenues: (1) more thorough and efficient cell screening during production, and (2) physically relevant information for more informed battery management strategies.