This Small Business Innovation Research (SBIR) Phase I project represents a major advance in battery research, combining the use of large, comprehensive battery datasets with advanced data science techniques and cloud-based software architectures to bring an unprecedented level of analytical capability to the problem of modeling battery performance. Past efforts at developing battery performance models have relied upon manufacturers performance data and limited single-discharge studies. This innovation applies contemporary data science techniques to the analysis of a large, normalized set of battery data including raw time-series data and aggregated per-cycle performance from many battery cycling tests, as well as "lab notebook" data including cell composition, dimensions, test methods, and observations. The result will be the first commercially-available tool for conducting comprehensive, multi-parameter empirical studies of battery performance. This unique, data-driven analytical capability will suggest new and promising research paths distilled from relationships hidden in the data, and will help to predict battery performance and lifetime. The broader impact/commercial potential of this project is manifested in its potential to dramatically increase the pace of product innovation and improvement in the battery sector. Organizations developing new batteries and those integrating batteries into their products will perform more targeted and effective battery tests, and will gain deeper insights from the data more quickly. Furthermore, our predictive analytics module will become more effective as the total volume of battery performance data stored in the system increases, further accelerating the pace of development. As this innovation is applicable to the entire spectrum of battery chemistries and designs, its successful implementation and commercialization will result in improvements in performance and reliability of batteries and battery-powered devices across a wide range of applications; from smartphones and tablets, to medical devices, to electric vehicles, and grid-scale energy storage. Broad adoption of this software will accelerate the development and deployment of energy storage and alternative energy technologies, promoting economic growth, energy independence, and environmental benefits. Market research suggests a total addressable market of up to $600M per year for this battery data platform with advance predictive analytics.
