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Battery State-of-Health (SOH) Estimation

Master advanced techniques for estimating and tracking battery health degradation using modern estimation methods.

Master advanced techniques for estimating and tracking battery health degradation using modern estimation methods.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Algorithms for Battery Management Systems Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.7

(155 ratings)

14,543 already enrolled

Instructors:

English

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Battery State-of-Health (SOH) Estimation

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Understand lithium-ion cell degradation mechanisms

  • Implement total capacity estimation methods

  • Calculate confidence intervals for estimates

  • Compute equivalent series resistance

  • Develop Kalman filter-based estimators

  • Evaluate different estimation approaches

Skills you'll gain

Battery Health Analysis
State Estimation
Degradation Mechanisms
Total Capacity Estimation
Resistance Estimation
Kalman Filtering
Statistical Methods
Battery Systems
Least Squares
Parameter Estimation

This course includes:

5.7 Hours PreRecorded video

31 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 6 modules in this course

This comprehensive course explores methods for estimating and tracking battery state-of-health, focusing on lithium-ion cell degradation mechanisms and estimation techniques. Students learn about capacity decrease and resistance increase phenomena, implementing various estimation methods including weighted least squares and Kalman filtering approaches. The curriculum covers both theoretical foundations and practical implementation using Octave/MATLAB, including confidence interval computation and parameter estimation techniques.

How does lithium-ion cell health degrade?

Module 1 · 4 Hours to complete

Total-least-squares battery-cell capacity estimation

Module 2 · 3 Hours to complete

Simplified total-least-squares battery-cell capacity estimates

Module 3 · 3 Hours to complete

How to write code for the different total-capacity estimators

Module 4 · 4 Hours to complete

A Kalman-filter approach to total capacity estimation

Module 5 · 3 Hours to complete

Capstone project

Module 6 · 3 Hours to complete

Fee Structure

Instructor

Gregory Plett
Gregory Plett

5 rating

22 Reviews

72,282 Students

9 Courses

Leading Expert in Battery Systems and Control Engineering

Gregory Plett serves as Professor of Electrical and Computer Engineering at the University of Colorado Colorado Springs, where he has established himself as a pioneering researcher in battery management systems since 1998. His academic credentials include a B.Eng. from Carleton University and M.S.E.E. and Ph.D. degrees from Stanford University. His research focuses on advanced control systems for high-capacity batteries used in hybrid and electric vehicles, encompassing physics-based modeling, system identification, and state estimation. He has authored three influential volumes on Battery Management Systems, covering battery modeling, equivalent-circuit methods, and physics-based methods. As Director of the UCCS High-Capacity Battery Research and Test Laboratory, he leads cutting-edge research in battery pack simulation and management systems. His teaching portfolio includes advanced courses in control systems, battery dynamics, and management algorithms. A senior member of IEEE and life member of the Electrochemical Society, his work has significantly influenced the field of electric vehicle battery technology. His research innovations include developing methods for state-of-charge estimation, degradation modeling, and fast-charging protocols for battery packs.

Battery State-of-Health (SOH) Estimation

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.7 course rating

155 ratings

Frequently asked questions

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