University of Colorado Boulder
Battery State-of-Charge (SOC) Estimation
University of Colorado Boulder

Battery State-of-Charge (SOC) 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

18,201 already enrolled

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

4.8

(244 reviews)

|

96%

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

What you'll learn

  • How to implement state-of-charge (SOC) estimators for lithium-ion battery cells

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

37 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(244 reviews)

|

96%

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

See how employees at top companies are mastering in-demand skills

Placeholder

Build your subject-matter expertise

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.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 7 modules in this course

This week, you will learn some rigorous definitions needed when discussing SOC estimation and some simple but poor methods to estimate SOC. As background to learning some better methods, we will review concepts from probability theory that are needed to be able to deal with the impact of uncertain noises on a system's internal state and measurements made by a BMS.

What's included

8 videos15 readings7 quizzes1 discussion prompt1 ungraded lab

This week, you will learn how to derive the steps of the Gaussian sequential probabilistic inference solution, which is the basis for all Kalman-filtering style state estimators. While this content is highly theoretical, it is important to have a solid foundational understanding of these topics in practice, since real applications often violate some of the assumptions that are made in the derivation, and we must understand the implication this has on the process. By the end of the week, you will know how to derive the linear Kalman filter.

What's included

6 videos6 readings6 quizzes

The steps of a Kalman filter may appear abstract and mysterious. This week, you will learn different ways to think about and visualize the operation of the linear Kalman filter to give better intuition regarding how it operates. You will also learn how to implement a linear Kalman filter in Octave code, and how to evaluate outputs from the Kalman filter.

What's included

7 videos7 readings7 quizzes2 ungraded labs

A linear Kalman filter can be used to estimate the internal state of a linear system. But, battery cells are nonlinear systems. This week, you will learn how to approximate the steps of the Gaussian sequential probabilistic inference solution for nonlinear systems, resulting in the "extended Kalman filter" (EKF). You will learn how to implement the EKF in Octave code, and how to use the EKF to estimate battery-cell SOC.

What's included

8 videos8 readings7 quizzes3 ungraded labs

The EKF is the best known and most widely used nonlinear Kalman filter. But, it has some fundamental limitations that limit its performance for "very nonlinear" systems. This week, you will learn how to derive the sigma-point Kalman filter (sometimes called an "unscented Kalman filter") from the Gaussian sequential probabilistic inference steps. You will also learn how to implement this filter in Octave code and how to use it to estimate battery cell SOC.

What's included

7 videos7 readings6 quizzes2 ungraded labs

Kalman filtering requires that noises have zero mean. What do we do if the current-sensor has a dc bias error, as is often the case? How can we implement Kalman-filter type SOC estimators in a computationally efficient way for a battery pack comprising many cells? This week you will learn how to compensate for current-sensor bias error and how to implement the bar-delta method for computational efficiency. You will also learn about desktop validation as an approach for initial testing and tuning of BMS algorithms.

What's included

5 videos5 readings4 quizzes1 ungraded lab

You have already learned that Kalman filters must be "tuned" by adjusting their process-noise, sensor-noise, and initial state-estimate covariance matrices in order to give acceptable performance over a wide range of operating scenarios. This final course module will give you some experience hand-tuning both an EKF and SPKF for SOC estimation.

What's included

2 programming assignments2 ungraded labs

Instructor

Instructor ratings
4.8 (79 ratings)
Gregory Plett
University of Colorado System
5 Courses67,162 learners

Offered by

Recommended if you're interested in Electrical Engineering

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

Showing 3 of 244

4.8

244 reviews

  • 5 stars

    80.73%

  • 4 stars

    16.80%

  • 3 stars

    1.63%

  • 2 stars

    0.40%

  • 1 star

    0.40%

ZZ
5

Reviewed on Jan 17, 2022

DB
4

Reviewed on Apr 14, 2021

RS
5

Reviewed on Feb 23, 2022

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions