Microsoft

Using Machine Learning to Translate In-Situ Battery Measurements to Optimize Battery Performance

In collaboration with Microsoft, this team developed a machine-learning pipeline to track the contributing factors behind battery swell in Microsoft Copilot PCs. Battery swell is a persistent issue in lithium batteries that arises from electrochemical processes that current methods cannot effectively predict from within the device. This project aims to monitor and estimate swell using on-device resources, enabling better control of its progression. To this end, the students analyzed extensive battery data gathered by Microsoft’s Battery Lab to identify the features most correlated with swell and developed scripts to capture device data and feed it into our prediction model.