Battery Pack Balancing and Power Estimation
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Battery Pack Balancing and Power Estimation
This course is part of Algorithms for Battery Management Systems Specialization
Instructor: Gregory Plett
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What you'll learn
How to design balancers and power-limits estimators for lithium-ion battery packs
Skills you'll gain
Tools you'll learn
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29 assignments
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There are 6 modules in this course
This course can also be taken for academic credit as ECEA 5734, part of CU Boulderβs 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
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 videos15 readings6 assignments1 discussion prompt
7 videosβ’Total 79 minutes
- 5.1.1: Welcome to the course!β’7 minutes
- 5.1.2: Introduction to battery-pack balancingβ’10 minutes
- 5.1.3: How do battery packs become imbalanced?β’16 minutes
- 5.1.4: What are the criteria for specifying a balancing setpoint for a battery pack?β’14 minutes
- 5.1.5: What are the criteria for specifying when to balance a battery pack?β’13 minutes
- 5.1.6: What kinds of circuits can be used for passively balancing a battery pack?β’16 minutes
- 5.1.7: Summary of "Passive balancing methods for battery packs"; what next?β’3 minutes
15 readingsβ’Total 45 minutes
- Course Updates and Accessibility Supportβ’1 minute
- Non-Credit Students: Welcome and Where to Find Helpβ’10 minutes
- Get help and meet other learners in this course. Join your discussion forums!β’2 minutes
- Notes for lesson 5.1.1β’1 minute
- Frequently asked questionsβ’5 minutes
- Course Resourcesβ’5 minutes
- How to use discussion forumsβ’5 minutes
- Earn a certificateβ’5 minutes
- Are you interested in earning an MSEE degree?β’5 minutes
- Notes for lesson 5.1.2β’1 minute
- Notes for lesson 5.1.3β’1 minute
- Notes for lesson 5.1.4β’1 minute
- Notes for lesson 5.1.5β’1 minute
- Notes for lesson 5.1.6β’1 minute
- Notes for lesson 5.1.7β’1 minute
6 assignmentsβ’Total 75 minutes
- Quiz for week 1β’30 minutes
- Practice quiz for lesson 5.1.2β’9 minutes
- Practice quiz for lesson 5.1.3β’9 minutes
- Practice quiz for lesson 5.1.4β’9 minutes
- Practice quiz for lesson 5.1.5β’9 minutes
- Practice quiz for lesson 5.1.6β’9 minutes
1 discussion promptβ’Total 10 minutes
- Introduce Yourselfβ’10 minutes
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 assignments1 ungraded lab
6 videosβ’Total 73 minutes
- 5.2.1: How to balance actively using capacitor-based circuitsβ’12 minutes
- 5.2.2: How to balance actively using transformer-based circuitsβ’8 minutes
- 5.2.3: How to balance actively using a shared active busβ’15 minutes
- 5.2.4: Using simulation to show how quickly we must balance a battery packβ’14 minutes
- 5.2.5: Introducing Octave code to simulate balancing: The main program loopβ’22 minutes
- 5.2.6: Summary of "Active balancing methods for battery packs"; what next?β’3 minutes
6 readingsβ’Total 6 minutes
- Notes for lesson 5.2.1β’1 minute
- Notes for lesson 5.2.2β’1 minute
- Notes for lesson 5.2.3β’1 minute
- Notes for lesson 5.2.4β’1 minute
- Notes for lesson 5.2.5β’1 minute
- Notes for lesson 5.2.6β’1 minute
6 assignmentsβ’Total 81 minutes
- Quiz for week 2β’30 minutes
- Practice quiz for lesson 5.2.1β’9 minutes
- Practice quiz for lesson 5.2.2β’9 minutes
- Practice quiz for lesson 5.2.3β’9 minutes
- Practice quiz for lesson 5.2.4β’9 minutes
- Practice quiz for lesson 5.2.5β’15 minutes
1 ungraded labβ’Total 30 minutes
- Notebook to run before attempting practice quizβ’30 minutes
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 assignments1 ungraded lab
5 videosβ’Total 44 minutes
- 5.3.1: What factors must we consider when finding available battery power?β’14 minutes
- 5.3.2: How to compute available battery power based on cell terminal voltageβ’8 minutes
- 5.3.3: How to consider other performance limits when computing available battery powerβ’8 minutes
- 5.3.4: Introducing Octave code to compute power limits using simplified cell modelβ’13 minutes
- 5.3.5: Summary of "How to find available battery power using a simplified cell model"; what next?β’2 minutes
5 readingsβ’Total 5 minutes
- Notes for lesson 5.3.1β’1 minute
- Notes for lesson 5.3.2β’1 minute
- Notes for lesson 5.3.3β’1 minute
- Notes for lesson 5.3.4β’1 minute
- Notes for lesson 5.3.5β’1 minute
5 assignmentsβ’Total 72 minutes
- Quiz for week 3 β’30 minutes
- Practice quiz for lesson 5.3.1β’9 minutes
- Practice quiz for lesson 5.3.2 β’9 minutes
- Practice quiz for lesson 5.3.3β’9 minutes
- Practice quiz for lesson 5.3.4β’15 minutes
1 ungraded labβ’Total 15 minutes
- Notebook to run before attempting practice quizβ’15 minutes
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 assignments3 ungraded labs
6 videosβ’Total 69 minutes
- 5.4.1: What factors must we consider when finding available battery power?β’13 minutes
- 5.4.2: How to solve for a future battery condition using the bisection algorithmβ’11 minutes
- 5.4.3: How to use bisection to estimate available power using comprehensive cell modelβ’17 minutes
- 5.4.4: Introducing Octave code to compute power limits using comprehensive cell modelβ’9 minutes
- 5.4.5: Using simulation to compare and contrast different power-estimation methodsβ’12 minutes
- 5.4.6: Concluding remarks for the specializationβ’6 minutes
6 readingsβ’Total 6 minutes
- Notes for lesson 5.4.1β’1 minute
- Notes for lesson 5.4.2β’1 minute
- Notes for lesson 5.4.3β’1 minute
- Notes for lesson 5.4.4β’1 minute
- Notes for lesson 5.4.5β’1 minute
- Notes for lesson 5.4.6β’1 minute
6 assignmentsβ’Total 119 minutes
- Quiz for week 4β’40 minutes
- Practice quiz for lesson 5.4.1β’9 minutes
- Practice quiz for lesson 5.4.2β’15 minutes
- Practice quiz for lesson 5.4.3β’15 minutes
- Practice quiz for lesson 5.4.4β’20 minutes
- Practice quiz for lesson 5.4.5β’20 minutes
3 ungraded labsβ’Total 50 minutes
- Notebook to run before attempting practice quizβ’10 minutes
- Notebook to run before attempting practice quizβ’10 minutes
- Notebook to run before attempting practice quizβ’30 minutes
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 videos7 readings6 assignments4 ungraded labs
6 videosβ’Total 138 minutes
- 5.5.1: What BMS algorithm needs remain?β’21 minutes
- 5.5.2: Physics-based ideal-cell modelsβ’17 minutes
- 5.5.3: Single-particle reduced-order modelsβ’31 minutes
- 5.5.4: 1-d Physics-Based Reduced-Order Modelsβ’20 minutes
- 5.5.5: Models of degradation mechanismsβ’18 minutes
- 5.5.6: Optimized controls using physics-based modelsβ’32 minutes
7 readingsβ’Total 16 minutes
- New Coursera policy on Honors badgesβ’10 minutes
- Notes for lesson 5.5.1β’1 minute
- Notes for lesson 5.5.2β’1 minute
- Notes for lesson 5.5.3β’1 minute
- Notes for lesson 5.5.4β’1 minute
- Notes for lesson 5.5.5β’1 minute
- Notes for lesson 5.5.6β’1 minute
6 assignmentsβ’Total 112 minutes
- Quiz for lesson 5.5.1β’20 minutes
- Quiz for lesson 5.5.2β’20 minutes
- Quiz for lesson 5.5.3β’20 minutes
- Quiz for lesson 5.5.4β’20 minutes
- Quiz for lesson 5.5.5β’20 minutes
- Quiz for lesson 5.5.6β’12 minutes
4 ungraded labsβ’Total 65 minutes
- Notebook to run before attempting quizβ’15 minutes
- Notebook to run before attempting quizβ’15 minutes
- Notebook to run before attempting quizβ’20 minutes
- Notebook to run before attempting quizβ’15 minutes
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
2 programming assignmentsβ’Total 30 minutes
- Part 1, Designing a Switched-Resistor Passive Balancing Systemβ’15 minutes
- Part 2, Improved HPPC power-limits estimatorβ’15 minutes
2 ungraded labsβ’Total 240 minutes
- Jupyter notebook for capstone project, Part 1β’120 minutes
- Jupyter notebook for capstone project, Part 2β’120 minutes
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Reviewed on Jan 24, 2023
This is a superb course and specialization. A big thanks to Prof Gregory and the rest of the team that made it happen.
Reviewed on Jul 20, 2023
Great content focusing on important aspects of the subject. It completes the rest of the courses in the specilization, and lays a good knowledge foundation on the subject.
Reviewed on Aug 27, 2024
I really liked how it was put together. Along with the books, this series of courses is very interesting for anyone who wants to learn more about the world of lithium batteries.
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