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
Этот курс входит в специализацию ''Специализация Algorithms for Battery Management Systems'
Battery Pack Balancing and Power Estimation
от партнера
Программа курса: что вы изучите
Неделя
13 ч. на завершение
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.
7 видео ((всего 79 мин.)), 11 материалов для самостоятельного изучения, 6 тестов
7 видео
5.1.2: Introduction to battery-pack balancing10мин
5.1.3: How do battery packs become imbalanced?15мин
5.1.4: What are the criteria for specifying a balancing setpoint for a battery pack?13мин
5.1.5: What are the criteria for specifying when to balance a battery pack?13мин
5.1.6: What kinds of circuits can be used for passively balancing a battery pack?16мин
5.1.7: Summary of "Passive balancing methods for battery packs"; what next?2мин
11 материала для самостоятельного изучения
Notes for lesson 5.1.11мин
Frequently Asked Questions5мин
Course Resources5мин
How to Use Discussion Forums5мин
Earn A Certificate5мин
Notes for lesson 5.1.21мин
Notes for lesson 5.1.31мин
Notes for lesson 5.1.41мин
Notes for lesson 5.1.51мин
Notes for lesson 5.1.61мин
Notes for lesson 5.1.71мин
6 практического упражнения
Practice quiz for lesson 5.1.29мин
Practice quiz for lesson 5.1.39мин
Practice quiz for lesson 5.1.49мин
Practice quiz for lesson 5.1.59мин
Practice quiz for lesson 5.1.69мин
Quiz for week 130мин
Неделя
23 ч. на завершение
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.
6 видео ((всего 73 мин.)), 6 материалов для самостоятельного изучения, 6 тестов
6 видео
5.2.2: How to balance actively using transformer-based circuits7мин
5.2.3: How to balance actively using a shared active bus14мин
5.2.4: Using simulation to show how quickly we must balance a battery pack14мин
5.2.5: Introducing Octave code to simulate balancing: The main program loop21мин
5.2.6: Summary of "Active balancing methods for battery packs"; what next?3мин
6 материала для самостоятельного изучения
Notes for lesson 5.2.11мин
Notes for lesson 5.2.21мин
Notes for lesson 5.2.31мин
Notes for lesson 5.2.41мин
Notes for lesson 5.2.51мин
Notes for lesson 5.2.61мин
6 практического упражнения
Practice quiz for lesson 5.2.19мин
Practice quiz for lesson 5.2.29мин
Practice quiz for lesson 5.2.39мин
Practice quiz for lesson 5.2.49мин
Practice quiz for lesson 5.2.515мин
Quiz for week 230мин
Неделя
32 ч. на завершение
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.
5 видео ((всего 44 мин.)), 5 материалов для самостоятельного изучения, 5 тестов
5 видео
5.3.2: How to compute available battery power based on cell terminal voltage8мин
5.3.3: How to consider other performance limits when computing available battery power7мин
5.3.4: Introducing Octave code to compute power limits using simplified cell model12мин
5.3.5: Summary of "How to find available battery power using a simplified cell model"; what next?1мин
5 материала для самостоятельного изучения
Notes for lesson 5.3.11мин
Notes for lesson 5.3.21мин
Notes for lesson 5.3.31мин
Notes for lesson 5.3.41мин
Notes for lesson 5.3.51мин
5 практического упражнения
Practice quiz for lesson 5.3.19мин
Practice quiz for lesson 5.3.29мин
Practice quiz for lesson 5.3.39мин
Practice quiz for lesson 5.3.415мин
Quiz for week 330мин
Неделя
44 ч. на завершение
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.
6 видео ((всего 69 мин.)), 6 материалов для самостоятельного изучения, 6 тестов
6 видео
5.4.2: How to solve for a future battery condition using the bisection algorithm11мин
5.4.3: How to use bisection to estimate available power using comprehensive cell model16мин
5.4.4: Introducing Octave code to compute power limits using comprehensive cell model9мин
5.4.5: Using simulation to compare and contrast different power-estimation methods12мин
5.4.6: Concluding remarks for the specialization6мин
6 материала для самостоятельного изучения
Notes for lesson 5.4.11мин
Notes for lesson 5.4.21мин
Notes for lesson 5.4.31мин
Notes for lesson 5.4.41мин
Notes for lesson 5.4.51мин
Notes for lesson 5.4.61мин
6 практического упражнения
Practice quiz for lesson 5.4.19мин
Practice quiz for lesson 5.4.215мин
Practice quiz for lesson 5.4.315мин
Practice quiz for lesson 5.4.420мин
Practice quiz for lesson 5.4.520мин
Quiz for week 440мин
Преподаватели
Gregory Plett
ProfessorElectrical and Computer Engineering
О Система университетов штата Колорадо
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.
О специализации ''Algorithms for Battery Management Systems'
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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