University of Colorado Boulder
Battery State-of-Health (SOH) Estimation
University of Colorado Boulder

Battery State-of-Health (SOH) Estimation

This course is part of Algorithms for Battery Management Systems Specialization

Taught in English

Some content may not be translated

Gregory Plett

Instructor: Gregory Plett

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Course

Gain insight into a topic and learn the fundamentals

4.7

(152 reviews)

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97%

Intermediate level
Some related experience required
22 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

What you'll learn

  • How to implement state-of-health (SOH) estimators for lithium-ion battery cells

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Assessments

31 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(152 reviews)

|

97%

Intermediate level
Some related experience required
22 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

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This course is part of the Algorithms for Battery Management Systems Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course

As battery cells age, their total capacities generally decrease and their resistances generally increase. This week, you will learn WHY this happens. You will learn about the specific physical and chemical mechanisms that cause degradation to lithium-ion battery cells. You will also learn why it is relatively simple to estimate and track changes to resistance, but why it is difficult to track changes to total capacity accurately.

What's included

8 videos13 readings7 quizzes1 discussion prompt1 ungraded lab

Total capacity is often estimated using ordinary-least-squares (OLS) methods. This week, you will learn that this is a fundamentally incorrect approach, and will learn that a total-least-squares (TLS) method should be used instead. You will learn how to derive a weighted OLS solution, to use as a benchmark, and how to derive a weighted TLS solution also.

What's included

7 videos7 readings7 quizzes4 ungraded labs

Unfortunately, the weighted TLS solution you learned in week 2 is not well suited for efficient computation on an embedded system like a BMS. As an intermediate step toward finding an efficient weighted TLS method, you will first learn a proportionally weighted TLS method this week. You will then learn how to generalize this to an "approximate weighted TLS" (AWTLS) method, which gives good estimates, and is feasible to implement on a BMS.

What's included

7 videos7 readings7 quizzes4 ungraded labs

So far this course, you have learned a number of methods for estimating total capacity. This week, you will learn how to implement those methods in Octave code. You will also explore different simulation scenarios to benchmark how well each method works, in comparison with the others. The scenarios are representative of hybrid-electric-vehicle (HEV) and battery-electric-vehicle (BEV) applications, but the principles learned can be extrapolated to other similar application domains.

What's included

6 videos6 readings6 quizzes5 ungraded labs

In the third course of the specialization, you learned how to use extended Kalman filters (EKFs) and sigma-point Kalman filters (SPKFs) to estimate the state of a battery cell. In this honors week, you will learn how to extend those concepts to apply EKF and SPKF to estimating the parameters of a battery-cell model if the state is known, and also how to simultaneously estimate both the state and parameters of a cell model.

What's included

6 videos6 readings4 quizzes2 ungraded labs

You have learned several different total-capacity estimation methods. Some of these methods work better than others in general, but any method is only as good as the data you give it. In this project, you will explore a different way to determine the "x" and "y" data you use as input to the total-capacity estimation methods.

What's included

1 programming assignment1 ungraded lab

Instructor

Instructor ratings
4.5 (26 ratings)
Gregory Plett
University of Colorado System
5 Courses67,610 learners

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Recommended if you're interested in Electrical Engineering

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