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Volver a Battery State-of-Charge (SOC) Estimation

Opiniones y comentarios de aprendices correspondientes a Battery State-of-Charge (SOC) Estimation por parte de Universidad de Colorado en Boulder

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Acerca del Curso

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...

Principales reseñas

NB

12 de ago. de 2021

As an electrical engineer, I firmly state that this course is the best for anyone who would like to embark on this journey of battery energy storage. Well structured

With an excellent instructor

BS

10 de ago. de 2020

Good and a very challenging course. Really makes you work to understand even the basic concepts. Challenging theoretical and practical assignments. Lot of learning obtained from this course

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