This course is part of the Algorithms for Battery Management Systems Specialization

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stars
86 ratings

Gregory Plett

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Offered By

University of Colorado Boulder

University of Colorado System

Part of the Master of Science in Electrical Engineering degree
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Algorithms for Battery Management Systems SpecializationUniversity of Colorado Boulder

About this Course

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This course can also be taken for academic credit as ECEA 5734, part of CU Boulder’s Master of Science in Electrical Engineering degree.
In this course, you will learn how to design balancing systems and to compute remaining energy and available power for a battery pack. By the end of the course, you will be able to:
-	Evaluate different design choices for cell balancing and articulate their relative merits
-	Design component values for a simple passive balancing circuit
-	Use provided Octave/MATLAB simulation tools to evaluate how quickly a battery pack must be balanced
-	Compute remaining energy and available power using a simple cell model
-	Use provided Octave/MATLAB script to compute available power using a comprehensive equivalent-circuit cell model

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Course 5 of 5 in the

Algorithms for Battery Management Systems Specialization

Intermediate Level

Approx. 22 hours to complete

English

What you will learn

How to design balancers and power-limits estimators for lithium-ion battery packs

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 5 in the

Algorithms for Battery Management Systems Specialization

Intermediate Level

Approx. 22 hours to complete

English

Instructor

Instructor rating

4.93/5 (17 Ratings)

Gregory Plett

Professor

Electrical and Computer Engineering

59,090 Learners

5 Courses

Offered by

University of Colorado Boulder

University of Colorado System

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Electrical Engineering from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Passive balancing methods for battery packs

In previous courses, you learned how to write algorithms to satisfy the estimation requirements of a battery management system. Now, you will learn how to write algorithms for two primary control tasks: balancing and power-limits computations. This week, you will learn why battery packs naturally become unbalanced, some balancing strategies, and how passive circuits can be used to balance battery packs.

3 hours to complete

7 videos (Total 79 min), 12 readings, 6 quizzes

7 videos

5.1.1: Welcome to the course!7m5.1.2: Introduction to battery-pack balancing10m5.1.3: How do battery packs become imbalanced?15m5.1.4: What are the criteria for specifying a balancing setpoint for a battery pack?13m5.1.5: What are the criteria for specifying when to balance a battery pack?13m5.1.6: What kinds of circuits can be used for passively balancing a battery pack?16m5.1.7: Summary of "Passive balancing methods for battery packs"; what next?2m

12 readings

Notes for lesson 5.1.11mFrequently asked questions5mCourse resources5mHow to use discussion forums5mEarn a certificate5mAre you interested in earning an MSEE degree?5mNotes for lesson 5.1.21mNotes for lesson 5.1.31mNotes for lesson 5.1.41mNotes for lesson 5.1.51mNotes for lesson 5.1.61mNotes for lesson 5.1.71m

6 practice exercises

Practice quiz for lesson 5.1.29mPractice quiz for lesson 5.1.39mPractice quiz for lesson 5.1.49mPractice quiz for lesson 5.1.59mPractice quiz for lesson 5.1.69mQuiz for week 130m

Week2

Week 2

3 hours to complete

Active balancing methods for battery packs

Passive balancing can be effective, but wastes energy. Active balancing methods attempt to conserve energy and have other advantages as well. This week, you will learn about active-balancing circuitry and methods, and will learn how to write Octave code to determine how quickly a battery pack can become out of balance. This is useful for determining the dominant factors leading to imbalance, and for estimating how quickly the pack must be balanced to maintain it in proper operational condition.

3 hours to complete

6 videos (Total 73 min), 6 readings, 6 quizzes

6 videos

5.2.1: How to balance actively using capacitor-based circuits11m5.2.2: How to balance actively using transformer-based circuits7m5.2.3: How to balance actively using a shared active bus14m5.2.4: Using simulation to show how quickly we must balance a battery pack14m5.2.5: Introducing Octave code to simulate balancing: The main program loop21m5.2.6: Summary of "Active balancing methods for battery packs"; what next?3m

6 readings

Notes for lesson 5.2.11mNotes for lesson 5.2.21mNotes for lesson 5.2.31mNotes for lesson 5.2.41mNotes for lesson 5.2.51mNotes for lesson 5.2.61m

6 practice exercises

Practice quiz for lesson 5.2.19mPractice quiz for lesson 5.2.29mPractice quiz for lesson 5.2.39mPractice quiz for lesson 5.2.49mPractice quiz for lesson 5.2.515mQuiz for week 230m

Week3

Week 3

2 hours to complete

How to find available battery power using a simplified cell model

2 hours to complete

5 videos (Total 44 min), 5 readings, 5 quizzes

5 videos

5.3.1: What factors must we consider when finding available battery power?13m5.3.2: How to compute available battery power based on cell terminal voltage8m5.3.3: How to consider other performance limits when computing available battery power7m5.3.4: Introducing Octave code to compute power limits using simplified cell model12m5.3.5: Summary of "How to find available battery power using a simplified cell model"; what next?1m

5 readings

Notes for lesson 5.3.11mNotes for lesson 5.3.21mNotes for lesson 5.3.31mNotes for lesson 5.3.41mNotes for lesson 5.3.51m

5 practice exercises

Practice quiz for lesson 5.3.19mPractice quiz for lesson 5.3.29mPractice quiz for lesson 5.3.39mPractice quiz for lesson 5.3.415mQuiz for week 330m

Week4

Week 4

4 hours to complete

How to find available battery power using a comprehensive cell model

The HPPC method, even as extended last week, makes some simplifying assumptions that are not met in practice. This week, we explore a more accurate method that uses full state information from an xKF as its input, along with a full ESC cell model to find power limits. You will learn how to implement this method in Octave code and will compare its computations to those from the HPPC method you learned about last week.

4 hours to complete

6 videos (Total 69 min), 6 readings, 6 quizzes

6 videos

5.4.1: What factors must we consider when finding available battery power?13m5.4.2: How to solve for a future battery condition using the bisection algorithm11m5.4.3: How to use bisection to estimate available power using comprehensive cell model16m5.4.4: Introducing Octave code to compute power limits using comprehensive cell model9m5.4.5: Using simulation to compare and contrast different power-estimation methods12m5.4.6: Concluding remarks for the specialization6m

6 readings

Notes for lesson 5.4.11mNotes for lesson 5.4.21mNotes for lesson 5.4.31mNotes for lesson 5.4.41mNotes for lesson 5.4.51mNotes for lesson 5.4.61m

6 practice exercises

Practice quiz for lesson 5.4.19mPractice quiz for lesson 5.4.215mPractice quiz for lesson 5.4.315mPractice quiz for lesson 5.4.420mPractice quiz for lesson 5.4.520mQuiz for week 440m

Reviews

4.9

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TOP REVIEWS FROM BATTERY PACK BALANCING AND POWER ESTIMATION

by ASAug 1, 2020

It is an excellent course for battery enthusiasts.

by SPJul 15, 2020

This is one of the best and most useful specialization in my eyes. I would encourage every person interested in EV domain to learn it. Thank you Dr Gregory Plett for this course

by NGSep 10, 2022

great to having this course help me out through such vast and eternal experines as in simple and effective way.

by DCMay 9, 2020

Especially the last Week 6 (Honors Course) was extremely useful, to better understand the advanced physical/chemical models for lithium batteries.

View all reviews

About the Algorithms for Battery Management Systems Specialization

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Battery Pack Balancing and Power Estimation

About this Course

What you will learn