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Battery State-of-Charge (SOC) Estimation

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...

By Gregory Plett on Coursera

About This Course

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: - Implement simple voltage-based and current-based state-of-charge estimators and understand their limitations - Explain the purpose of each step in the sequential-probabilistic-inference solution - Execute provided Octave/MATLAB script for a linear Kalman filter and evaluate results - Execute provided Octave/MATLAB script for state-of-charge estimation using an extended Kalman filter on lab-test data and evaluate results - Execute provided Octave/MATLAB script for state-of-charge estimation using a sigma-point Kalman filter on lab-test data and evaluate results - Implement method to detect and discard faulty voltage-sensor measurements

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Frequently Asked Questions

How much does Battery State-of-Charge (SOC) Estimation cost?

Visit the Battery State-of-Charge (SOC) Estimation course page for current pricing and available discounts.

Who teaches Battery State-of-Charge (SOC) Estimation?

Battery State-of-Charge (SOC) Estimation is taught by Gregory Plett, University of Colorado Boulder.

What skill level is Battery State-of-Charge (SOC) Estimation for?

This course is designed for all levels learners.

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DurationSelf-paced
LevelAll Levels
Languageen
PlatformCoursera