Systems and methods for cell-based modeling performance of a battery pack

A computer-implemented method for estimating a property of an energy storage system, comprising:

• receiving sensor data associated with the energy storage system;
• transforming, using a mapping model executing on at least one hardware computer processor, the sensor data into cell-level data for representative cells of the energy storage system;
• providing the cell-level data as input to a trained machine learning (ML) model;
• and
• estimating the property of the energy storage system using the trained ML model.

A computer-implemented method, comprising:

• receiving first sensor data associated with an energy storage system;
• transforming, using at least one hardware computer processor, the first sensor data into cell-level data for a number of representative cells in the energy storage system;
• generating a mapping model configured to transform second sensor data into cell-level data for representative cells in the energy storage system, wherein the mapping model is generated based, at least in part, on the cell-level data for the number of representative cells and the first sensor data;
• and
• outputting the generated mapping model.