Battery State-of-Health (SOH) Estimation

 

As the world increasingly transitions to electric vehicles and renewable energy solutions, understanding battery health becomes crucial. Coursera offers an excellent course titled "Battery State-of-Health (SOH) Estimation," part of the "Algorithms for Battery Management Systems" specialization, designed by the University of Colorado Boulder. This course provides in-depth knowledge on implementing state-of-health estimators for lithium-ion batteries, which are widely used in electric vehicles and various portable electronic devices.

Course Overview

The "Battery State-of-Health (SOH) Estimation" course spans six weeks and covers a range of topics essential for understanding and estimating battery health:

1. Week 1: Degradation Mechanisms

   • Learn about the primary degradation mechanisms affecting lithium-ion cells and the challenges in estimating total capacity and resistance over time.

2. Week 2: Total-Least-Squares Battery-Cell Capacity Estimation

   • Understand why ordinary-least-squares methods are insufficient for capacity estimation and how to apply total-least-squares methods instead.

3. Week 3: Simplified Estimation Methods

   • Explore proportionally weighted and approximate weighted total-least-squares methods that are computationally feasible for battery management systems (BMS).

4. Week 4: Coding Total-Capacity Estimators

   • Implement the learned estimation methods in Octave/MATLAB and benchmark their performance in various simulation scenarios.

5. Week 5: Kalman Filter Approach

   • Apply extended Kalman filters (EKFs) and sigma-point Kalman filters (SPKFs) for both state and parameter estimation in battery cells.

6. Week 6: Capstone Project

   • Utilize different data inputs to improve total-capacity estimation methods and demonstrate proficiency in the concepts learned throughout the course.

Learning Outcomes

By the end of the course, participants will be able to:

• Identify and understand the key degradation mechanisms in lithium-ion batteries.
• Implement various state-of-health estimation methods using Octave/MATLAB scripts.
• Compute confidence intervals for capacity estimates and equivalent-series resistance.
• Balance the tradeoffs between different estimation approaches to ensure robust performance.

Course Structure and Requirements

This intermediate-level course requires a commitment of 1-4 hours per week over a period of 5-12 weeks. It is part of a larger specialization that includes other courses on battery management systems, covering topics from basic battery operation to advanced state-of-charge and power estimation techniques​ 

Enrollment and Certification : Battery State-of-Health (SOH) Estimation

Participants can audit the course for free, but those seeking a certificate must pay a fee. Financial aid is available for those who qualify. The course is available in multiple languages, including English, French, Portuguese, Russian, and Spanish, making it accessible to a global audience​ ​​ 

Practical Applications

This course is particularly beneficial for professionals in the fields of electrical engineering, automotive engineering, and renewable energy, as well as researchers and students interested in battery technology. The skills gained can be directly applied to real-world projects involving electric vehicles, portable electronics, and grid energy storage systems.