University of Colorado Boulder
Battery Pack Balancing and Power Estimation
University of Colorado Boulder

Battery Pack Balancing and Power 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

10,900 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.9

(97 reviews)

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

What you'll learn

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

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Assessments

29 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.9

(97 reviews)

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

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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.
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There are 6 modules in this course

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.

What's included

7 videos13 readings6 quizzes1 discussion prompt

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.

What's included

6 videos6 readings6 quizzes1 ungraded lab

This week, we begin by reviewing the HPPC power-limit method from course 1. Then, you will learn how to extend the method to satisfy limits on SOC, load power, and electronics current. You will learn how to implement the power-limits computation methods in Octave code, and will see results for a representative scenario.

What's included

5 videos5 readings5 quizzes1 ungraded lab

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.

What's included

6 videos6 readings6 quizzes3 ungraded labs

Present-day BMS algorithms primarily use equivalent-circuit models as a basis for estimating state-of-charge, state-of-health, power limits, and so forth. These models are not able to describe directly the physical processes internal to the cell. But, it is exactly these processes that are precursors to cell degradation and failure. This week quickly introduces some concepts that might motivate future BMS algorithms that use physics-based models instead.

What's included

6 videos6 readings6 quizzes4 ungraded labs

This capstone project explores the design of resistor value for a switched-resistor passive balancing system as well as enhancing a power-limits method based on the HPPC approach.

What's included

2 programming assignments2 ungraded labs

Instructor

Instructor ratings
5.0 (22 ratings)
Gregory Plett
University of Colorado System
5 Courses68,460 learners

Offered by

Recommended if you're interested in Electrical Engineering

Get a head start on your degree

This course is part of the following degree programs offered by University of Colorado Boulder. If you are admitted and enroll, your coursework can count toward your degree learning and your progress can transfer with you.

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