TUT8: Battery Data Science for Automotive Applications

ABOUT THIS TUTORIAL:

From the manufacturing floor to on-board vehicle diagnostics, each battery represents a potentially valuable stream of data. This tutorial will focus on a broad survey of "data science" tools that can help make these data streams useful.

TOPICS TO BE COVERED:

• Data management: Security, the “cloud”, datastores
• Data exploration: Tools for working with large data sets
• Machine learning: Matching the algorithm to the problem

WHO SHOULD ATTEND:

Engineers and scientists working for materials and component companies, battery developers, pack developers, and OEMS; data scientists; and business development and technical sales who are looking to gain a deeper understanding of the product and development process.

INSTRUCTOR:

Matthew Murbach, PhD, CTO, Hive Battery Labs

Matt has a PhD in Chemical Engineering with Advanced Data Science from the University of Washington. His PhD research focused on the physics-based modeling of impedance for lithium-ion batteries and he has experience developing software for battery management and impedance analysis.

Back to Tutorials