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Battery State-of-Charge (SOC) Estimation

Algorithms for Battery Management Systems,

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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Rating 4.0 based on 1 ratings
Length 8 weeks
Starts Aug 17 (6 weeks ago)
Cost $49
From University of Colorado System via Coursera
Instructor Gregory Plett
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Engineering
Tags Computer Science Algorithms Physical Science And Engineering Electrical Engineering

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What people are saying

course into kalman

Overall, I good introductory course into Kalman Filtering for SOC estimation.

filter algorithm relating

In addition to tuning the initial covariance states, maybe add a different part 2 (other than tuning initial parameters) for developing to understand the kalman filter algorithm relating to battery estimation.

good introductory course

filtering for soc

add a different

covariance states

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Rating 4.0 based on 1 ratings
Length 8 weeks
Starts Aug 17 (6 weeks ago)
Cost $49
From University of Colorado System via Coursera
Instructor Gregory Plett
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Engineering
Tags Computer Science Algorithms Physical Science And Engineering Electrical Engineering

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