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:
This course is part of the Algorithms for Battery Management Systems Specialization
Offered By
University of Colorado Boulder
University of Colorado System
Algorithms for Battery Management Systems SpecializationUniversity of Colorado BoulderAbout this Course
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Course 5 of 5 in the
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Intermediate Level
Approx. 22 hours to complete
English
Subtitles: English
What you will learn
How to design balancers and power-limits estimators for lithium-ion battery packs
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 5 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 22 hours to complete
English
Subtitles: English
Offered by
University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
University of Colorado System
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
Syllabus - What you will learn from this course
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), 11 readings, 6 quizzes
7 videos
5.1.2: Introduction to battery-pack balancing10m
5.1.3: How do battery packs become imbalanced?15m
5.1.4: What are the criteria for specifying a balancing setpoint for a battery pack?13m
5.1.5: What are the criteria for specifying when to balance a battery pack?13m
5.1.6: What kinds of circuits can be used for passively balancing a battery pack?16m
5.1.7: Summary of "Passive balancing methods for battery packs"; what next?2m
11 readings
Notes for lesson 5.1.11m
Frequently asked questions5m
Course resources5m
How to use discussion forums5m
Earn a certificate5m
Notes for lesson 5.1.21m
Notes for lesson 5.1.31m
Notes for lesson 5.1.41m
Notes for lesson 5.1.51m
Notes for lesson 5.1.61m
Notes for lesson 5.1.71m
6 practice exercises
Practice quiz for lesson 5.1.29m
Practice quiz for lesson 5.1.39m
Practice quiz for lesson 5.1.49m
Practice quiz for lesson 5.1.59m
Practice quiz for lesson 5.1.69m
Quiz for week 130m
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
5.2.2: How to balance actively using transformer-based circuits7m
5.2.3: How to balance actively using a shared active bus14m
5.2.4: Using simulation to show how quickly we must balance a battery pack14m
5.2.5: Introducing Octave code to simulate balancing: The main program loop21m
5.2.6: Summary of "Active balancing methods for battery packs"; what next?3m
6 readings
Notes for lesson 5.2.11m
Notes for lesson 5.2.21m
Notes for lesson 5.2.31m
Notes for lesson 5.2.41m
Notes for lesson 5.2.51m
Notes for lesson 5.2.61m
6 practice exercises
Practice quiz for lesson 5.2.19m
Practice quiz for lesson 5.2.29m
Practice quiz for lesson 5.2.39m
Practice quiz for lesson 5.2.49m
Practice quiz for lesson 5.2.515m
Quiz for week 230m
2 hours to complete
How to find available battery power using a simplified cell model
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.
2 hours to complete
5 videos (Total 44 min), 5 readings, 5 quizzes
5 videos
5.3.2: How to compute available battery power based on cell terminal voltage8m
5.3.3: How to consider other performance limits when computing available battery power7m
5.3.4: Introducing Octave code to compute power limits using simplified cell model12m
5.3.5: Summary of "How to find available battery power using a simplified cell model"; what next?1m
5 readings
Notes for lesson 5.3.11m
Notes for lesson 5.3.21m
Notes for lesson 5.3.31m
Notes for lesson 5.3.41m
Notes for lesson 5.3.51m
5 practice exercises
Practice quiz for lesson 5.3.19m
Practice quiz for lesson 5.3.29m
Practice quiz for lesson 5.3.39m
Practice quiz for lesson 5.3.415m
Quiz for week 330m
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
5.4.2: How to solve for a future battery condition using the bisection algorithm11m
5.4.3: How to use bisection to estimate available power using comprehensive cell model16m
5.4.4: Introducing Octave code to compute power limits using comprehensive cell model9m
5.4.5: Using simulation to compare and contrast different power-estimation methods12m
5.4.6: Concluding remarks for the specialization6m
6 readings
Notes for lesson 5.4.11m
Notes for lesson 5.4.21m
Notes for lesson 5.4.31m
Notes for lesson 5.4.41m
Notes for lesson 5.4.51m
Notes for lesson 5.4.61m
6 practice exercises
Practice quiz for lesson 5.4.19m
Practice quiz for lesson 5.4.215m
Practice quiz for lesson 5.4.315m
Practice quiz for lesson 5.4.420m
Practice quiz for lesson 5.4.520m
Quiz for week 440m
Reviews
TOP REVIEWS FROM BATTERY PACK BALANCING AND POWER ESTIMATION
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 SGAug 4, 2020
Professor visualization is excellent and his explanation is extraordinary with the material.I am very Happy to complete this course and very Informative.
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.
by RGApr 13, 2020
Volveré. Y lo pagaré. Este y los otros cuatro cursos. Porque quiero esos certificados.
About the Algorithms for Battery Management Systems Specialization
In this specialization, you will learn the major functions that must be performed by a battery management system, how lithium-ion battery cells work and how to model their behaviors mathematically, and how to write algorithms (computer methods) to estimate state-of-charge, state-of-health, remaining energy, and available power, and how to balance cells in a battery pack.
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Is financial aid available?
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Will I earn university credit for completing the Course?
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