Jacob Sass

Jacob Sass is a graduate student in chemical engineering breaking new ground in the simulation, optimization, and control of battery systems. His research tackles the growing need for more reliable, efficient, and interpretable models that support decision-making in battery design and operation. Jacob focuses on integrating data-driven and physics-based approaches to improve the performance and lifespan of lithium-ion batteries. He has developed interpretable machine learning models to predict battery aging from manufacturing data, utilizing MATLAB tools such as fscmrmr and fitrgam for feature selection and model training. He currently builds high-fidelity physics-based battery simulations. As a MathWorks Fellow, Jacob will build efficient implementations of multiphase battery models for real-time control applications, comparing the results with those from the MATLAB battery simulation package, Li-ION SIMulation BAttery Toolbox. His work could inform optimal charging strategies for electric vehicles while minimizing degradation and improving battery lifespans in high-rate scenarios.