Battery State-of-Charge (SOC) Estimation
This course is part of Algorithms for Battery Management Systems.
Course Cost
Free course
Intermediate
Skill Level
25 Hours
Self-paced lessons
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.
What you'll learn
Implement voltage and current-based SOC estimators
Apply sequential probabilistic inference methods
Execute linear Kalman filter implementations
Develop extended Kalman filter solutions
Implement sigma-point Kalman filter techniques
Handle faulty sensor measurements
Skills you'll gain
This course includes:
8.1 Hours PreRecorded video
37 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Closed caption

Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.





There are 7 modules in this course
This comprehensive course covers advanced techniques for estimating battery state-of-charge (SOC). Students learn to implement and evaluate various estimation methods, from basic voltage-based approaches to sophisticated Kalman filtering techniques. The curriculum progresses through linear Kalman filters, extended Kalman filters (EKF), and sigma-point Kalman filters (SPKF), with practical implementation in Octave/MATLAB. Special attention is given to handling sensor errors and improving computational efficiency for battery pack applications.
The importance of a good SOC estimator
Module 1 · 5 Hours to complete
Introducing the linear Kalman filter as a state estimator
Module 2 · 3 Hours to complete
Coming to understand the linear Kalman filter
Module 3 · 3 Hours to complete
Cell SOC estimation using an extended Kalman filter
Module 4 · 4 Hours to complete
Cell SOC estimation using a sigma-point Kalman filter
Module 5 · 4 Hours to complete
Improving computational efficiency using the bar-delta method
Module 6 · 2 Hours to complete
Capstone project
Module 7 · 4 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Algorithms for Battery Management Systems
Reviews
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.
Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.




