Enroll Course: https://www.coursera.org/learn/battery-state-of-charge
Overview of the Course
The world of battery technology is more critical than ever, especially with the rise of electric vehicles and renewable energy storage. Understanding the state-of-charge (SOC) of a battery isn’t just useful; it’s essential for optimizing battery performance, lifespan, and safety. The Battery State-of-Charge (SOC) Estimation course on Coursera dives deep into the methodologies for estimating SOC, preparing students for real-world challenges in electrical engineering.
What You’ll Learn
This course offers a comprehensive approach to SOC estimation through theoretical concepts and practical applications. By the end of the course, you’ll be able to:
- Implement voltage-based and current-based SOC estimators and discern their limitations.
- Understand and apply probabilistic inference techniques, essential for dealing with uncertainties in battery management systems (BMS).
- Utilize a range of Kalman filters, including the linear Kalman filter, the extended Kalman filter, and the sigma-point Kalman filter, to improve SOC estimation accuracy.
- Enhance computational efficiency in SOC algorithms, especially for complex systems with many cells.
Course Structure
The course is divided into modules that gradually build your understanding:
- The importance of a good SOC estimator: Learn about SOC definitions and explore initial methods that highlight the need for robust estimating techniques.
- Introducing the linear Kalman filter: Delve into the theoretical underpinnings of Kalman filters and their relevance in practical applications.
- Understanding the linear Kalman filter: Visualize and implement the filter in Octave, leading to a deeper intuition of its operations.
- Cell SOC estimation using an extended Kalman filter: Transition from linear to nonlinear systems with the EKF, including hands-on coding exercises.
- Using a sigma-point Kalman filter: Learn advanced methods for tackling highly nonlinear systems and apply these techniques to SOC estimation.
- Improving computational efficiency: Address challenges around sensor bias and learn the bar-delta method for efficient estimation.
- Capstone project: Put your knowledge to the test by tuning both EKF and SPKF for real-world SOC scenarios.
Who Should Take This Course?
This course is perfect for electrical engineering students, professionals in the battery technology industry, and anyone interested in deepening their understanding of battery management systems. Because it also counts for academic credit as ECEA 5732 at CU Boulder, it’s an excellent option for students pursuing a Master of Science in Electrical Engineering.
Final Thoughts
The Battery State-of-Charge (SOC) Estimation course is a well-structured offering that balances theoretical knowledge and practical skills. If you’re serious about excelling in the field of battery technology, mastering SOC estimation methods is imperative. I highly recommend enrolling in this course on Coursera to not only enhance your personal skill set but also to contribute meaningfully in a rapidly evolving industry.
Enroll Course: https://www.coursera.org/learn/battery-state-of-charge