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Back to Battery State-of-Health (SOH) Estimation

Learner Reviews & Feedback for Battery State-of-Health (SOH) Estimation by University of Colorado Boulder

4.7
stars
155 ratings

About the Course

This course can also be taken for academic credit as ECEA 5733, part of CU Boulder’s Master of Science in Electrical Engineering degree. In this course, you will learn how to implement different state-of-health estimation methods and to evaluate their relative merits. By the end of the course, you will be able to: - Identify the primary degradation mechanisms that occur in lithium-ion cells and understand how they work - Execute provided Octave/MATLAB script to estimate total capacity using WLS, WTLS, and AWTLS methods and lab-test data, and to evaluate results - Compute confidence intervals on total-capacity estimates - Compute estimates of a cell’s equivalent-series resistance using lab-test data - Specify the tradeoffs between joint and dual estimation of state and parameters, and steps that must be taken to ensure robust estimates (honors)...

Top reviews

MH

Sep 11, 2022

Very informative course that explain the causes of degradation happen on battey cells and how to estimate the main quantities that affect the battery health using different regression techniques.

AK

Sep 22, 2020

It was very new to me, and very interesting stuff. It became even better with the instructor's skill.

I would love recommending it to my friends

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1 - 25 of 43 Reviews for Battery State-of-Health (SOH) Estimation

By Davide C

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May 10, 2020

This course explains how to estimate battery SOH (State of Health) parameters: series resistance and total capacity, by using total least squares method and Kalman filters. Honestly, this course was quite boring compared to the other 4 courses of this specialization, but I found the mathematical methods explained in this course to be very useful. The Prof. explains very well and easily such complex concepts.

By Albert S

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Mar 2, 2020

This course provides detailed understanding into the state-of-health estimation theory. The course is a logical follow-up to the third course in this series (Battery State-of-Charge (SOC) Estimation). The underlying maths is somewhat more demanding than in the aforementioned course, therefore, taking more time to grasp on it would be benefitial. This course requires dilligent work at home as well. I would recommend it to anyone dealing with battery control algorithms, both at the university, as well as in the private sector.

By John W

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May 31, 2019

excellent course in different statistical methods (different least squares methods) of estimating capacity. So much to learn in such a condense course. Aside from many coding examples, the main purpose is to teach statistical methods for optimizing capacity estimation and evaluate the performance of different methods. Its really up to the learner how much time they like to spend, either observing every little coding detail, or to just learning the main ideas.

By Suresh K R

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Mar 11, 2020

This Course is one of best technique in the literature point of view to compute the SOH of Lithium ion battery with Estimation and Probability techniques. I sincerely thank Dr.Plett and his team , and also Coursera team for providing this course to me.

Thanks and Yours Sincerely

Suresh Kumar.R

By Roman F

•

Mar 29, 2023

This is really a remarkable course in which battery state of health is analyzed in details with discussion of theoretical background and with practical implementation of methods for estimating the resistance and total capacity of a cell

By Mahmoud H

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Sep 12, 2022

Very informative course that explain the causes of degradation happen on battey cells and how to estimate the main quantities that affect the battery health using different regression techniques.

By Anant k

•

Sep 23, 2020

It was very new to me, and very interesting stuff. It became even better with the instructor's skill.

I would love recommending it to my friends

By Apurv S

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Apr 9, 2020

A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.

By derick m

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Apr 18, 2023

Challenging and sufficient enough to impart the skills necessary to develop reliable battery management systems algorithms.

By Batteryand S

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Sep 3, 2023

I pray that I get financial aid and finish the last course because the journey has been a great success.

By Varun K

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May 30, 2020

Good course. Nice insight on optimization techniques. Problems and cases studies are really good

By JustinSmith

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May 24, 2022

Great course with a an emphasis on using the previous courses to create useful programs

By Sajad S

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Mar 30, 2024

Perfect course if you want to learn a to z of battery management system from scratch.

By Suryakant A K

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Aug 24, 2020

Gave brief overview of SOH and helps in understanding the basic concepts.

By Harish J

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Nov 14, 2022

tThank to give an best opportunityto learn moreasily

By Mateus L

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Aug 28, 2024

A great place to start understanding battery aging

By Shovan R S

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Oct 1, 2020

great course. very insightful

By Vinayak K

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Aug 15, 2019

Exceptional Professor!!

By SURAJ D

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Nov 15, 2022

i am health estimation

By HIMANSHU M

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Jun 26, 2023

Wonderful course...

By NANDHINI G

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Nov 17, 2022

good and useful

By ISAKKIRAJA P E 2

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Nov 17, 2022

good and super

By ROHAN R

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Nov 17, 2022

nice Course

By Dr. V K V

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Apr 21, 2021

Excellent

By Arun K

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Nov 15, 2022

super