Battery State-of-Charge (SOC) Estimation

In this specialization, you will learn the major functions that must be performed by a battery management system, how lithium-ion battery cells work and how to model their behaviors mathematically, and how to write algorithms (computer methods) to estimate state-of-charge, state-of-health, remaining energy, and available power, and how to balance cells in a battery pack.

( 2 Reviews )

Created by: Gregory Plett

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Overall Score : 80 / 100

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Course Description

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 an sigma-point Kalman filter on lab-test data and evaluate results-Implement method to detect and discard faulty voltage-sensor measurements

Time: 31h

Instructor Details

Gregory Plett

4.0 Rating
2 Reviews

CoursesBattery Pack Balancing and Power EstimationEquivalent Circuit Cell Model SimulationBattery State-of-Health (SOH) EstimationBattery State-of-Charge (SOC) EstimationIntroduction to battery-management systems