SBIR-STTR Award

The broader impact/commercial potential of this project lies in the ability of this technology to impact how every battery is made, tested, managed, and re-used in the near future. Batteries are ubiquitous, and their use is likely to increase in the future. As such, there is a growing need for low-cost, accurate methods for monitoring the state of charge (SOC) and the state of health (SOH) in real time to optimize performance and maximize lifetime. The technology that will be developed in this project will use ultrasound to noninvasively probe batteries and provide physical insights into SOC and SOH, and will work on any closed battery regardless of chemistry and form factor. Initial finding of this hypothesis have already been demonstrated and published. This is an unexplored area and presents a large commercial opportunity in each sector of the battery industry, including diagnostics, quality assurance, active cycling control, and the emerging second-life markets. Several advantages include sensitivity to subtle physical changes within cells, the ability to probe lab and commercial scale cells, and sub-millisecond readings. From battery R&D, to manufacturing, to management systems, ultrasound for batteries will help enable the efficient generation, storage, and use of energy worldwide. This Small Business Innovation Research (SBIR) Phase I project will support the development of this technology leading to the first commercial ultrasonic battery analysis unit. The feasibility of 1) miniaturized pulser-receivers with pulsing and switching speeds that are orders of magnitude faster than commercial units, and 2) miniaturized transducers that can transmit and receive high quality signals will be demonstrated. This would enable the detection of high-rate phenomena and the use of multiplexed systems. 3) The use of fast data analysis algorithms for real-time SOC prediction using acoustics as the main input will also be addressed. These objectives are necessary for demonstrating the applicability of ultrasonic analysis to the battery R&D, manufacturing, and second life markets. The success of Phase I of this project will lead to the development of micron-scale sensors for incorporation in battery management systems. In Phase II, algorithms for SOH prediction and cycling control based on acoustic data will be developed, as well as investigation of the design and fabrication of microelectronic transducers will be performed.

The broader impact/commercial potential of this project will be in helping batteries exceed the quality, performance, and safety demands of mass-market electric vehicles, renewable energy generation, and next-generation consumer electronic devices. The need for high-performance batteries is accelerating, and as batteries grow in energy density, size, and production volumes, so will the issues that persist with quality. Unless these issues are addressed, they will continue to have major implications for the performance, safety, and adoption of these important technologies. The challenge is that outside of R&D labs, the industry relies on essentially the same basic data as when batteries were first invented: voltage, current, and temperature. As a result, at commercial scales, only a small percentage of batteries are inspected in a meaningful way, with methods that only provide indirect information about physical condition. This Phase 2 project is focused on developing a new platform for production-level battery inspection that directly probes the physical condition of batteries with a high testing throughput. This could lead to better decisions in manufacturing environments and could decrease system costs, increase capacity and operational lifetime, and accelerate the scale-up of promising new materials.This Small Business Innovation Research (SBIR) Phase 2 project addresses the need for a physical mode of inspection in battery production environments that is capable of screening every cell with high fidelity. Currently, inspection in production-level environments are limited to electrical measurements and X-rays. Electrical methods provide only indirect and cell-averaged information about physical condition, and X-rays are not practically able to detect the distribution of electrolyte within batteries nor the formation of the solid electrolyte interphase (SEI) layer (both of which strongly affect long-term reliability, performance, and safety of batteries). This Phase 2 project aims to develop a platform that utilizes sound-based methods to inspect batteries in production-environments. This will involve developing a scaled, automated hardware system as well as software and computational methods for processing and analyzing the acoustic signals. The Phase 2 project will also include various testing and validation efforts to assess the ability of acoustic analysis to both directly determine the performance quality and reliability of cells beyond beginning of life capacity and resistance, as well as to improve the performance of strings of cells and modules.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.