Battery State of Charge (SOC)

This course can also be credited toward ECEA 5732, part of CU Boulder's Electrical Engineering Master of Science program. In this course, you will learn how to apply various state-of-charge estimation methods and evaluate their relative merits. By the end of the course, you will be able to: - Implement simple voltage- and current-based state-of-charge estimation methods and understand their limitations - Explain the purpose of each step in solving a sequential probabilistic inference - Run the provided Octave/MATLAB script for a linear Kalman filter and evaluate the results - Run the provided Octave/MATLAB script to estimate state-of-charge using an extended Kalman filter on lab test data and evaluate the results - Run the provided Octave/MATLAB script to estimate state-of-charge using a sigma-point Kalman filter on lab test data and evaluate the results - Implement a method to detect and discard erroneous voltage sensor measurements