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)
A great place to start understanding battery aging
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
Gave brief overview of SOH and helps in understanding the basic concepts.
Challenging and sufficient enough to impart the skills necessary to develop reliable battery management systems algorithms.
Good course. Nice insight on optimization techniques. Problems and cases studies are really good
tThank to give an best opportunityto learn moreasily
Great course with a an emphasis on using the previous courses to create useful programs
A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.
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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.
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.
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.
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
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
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.
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
A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.
Challenging and sufficient enough to impart the skills necessary to develop reliable battery management systems algorithms.
Good course. Nice insight on optimization techniques. Problems and cases studies are really good
Great course with a an emphasis on using the previous courses to create useful programs
Perfect course if you want to learn a to z of battery management system from scratch.
Gave brief overview of SOH and helps in understanding the basic concepts.
tThank to give an best opportunityto learn moreasily
A great place to start understanding battery aging
great course. very insightful
Exceptional Professor!!
i am health estimation
Wonderful course...