This course can also be taken for academic credit as ECEA 5732, part of CU Boulder s Master of Science in Electrical Engineering degree. In this course, you will learn how to implement different state-of-charge estimation methods and to evaluate their relative merits. By the end of the course, you will be able to: -\tImplement simple voltage-based and current-based state-of-charge estimators and understand their limitations -\tExplain the purpose of each step in the sequential-probabilistic-inference solution -\tExecute provided Octave/MATLAB script for a linear Kalman filter and evaluate results -\tExecute provided Octave/MATLAB script for state-of-charge estimation using an extended Kalman filter on lab-test data and evaluate results -\tExecute provided Octave/MATLAB script for state-of-charge estimation using a sigma-point Kalman filter on lab-test data and evaluate results -\tImplement method to detect and discard faulty voltage-sensor measurements