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
Este curso faz parte do Programa de cursos integrados Algorithms for Battery Management Systems
Battery Pack Balancing and Power Estimation
oferecido por
Programa de cursos integrados Algorithms for Battery Management SystemsUniversity of Colorado System
Programa - O que você aprenderá com este curso
Semana
1Passive 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.
11 leituras, 6 testes
11 leituras
Notes for lesson 5.1.11min
Frequently Asked Questions5min
Course Resources5min
How to Use Discussion Forums5min
Earn A Certificate5min
Notes for lesson 5.1.21min
Notes for lesson 5.1.31min
Notes for lesson 5.1.41min
Notes for lesson 5.1.51min
Notes for lesson 5.1.61min
Notes for lesson 5.1.71min
6 exercícios práticos
Practice quiz for lesson 5.1.29min
Practice quiz for lesson 5.1.39min
Practice quiz for lesson 5.1.49min
Practice quiz for lesson 5.1.59min
Practice quiz for lesson 5.1.69min
Quiz for week 130min
Semana
2Active 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 leituras, 6 testes
6 leituras
Notes for lesson 5.2.11min
Notes for lesson 5.2.21min
Notes for lesson 5.2.31min
Notes for lesson 5.2.41min
Notes for lesson 5.2.51min
Notes for lesson 5.2.61min
6 exercícios práticos
Practice quiz for lesson 5.2.19min
Practice quiz for lesson 5.2.29min
Practice quiz for lesson 5.2.39min
Practice quiz for lesson 5.2.49min
Practice quiz for lesson 5.2.515min
Quiz for week 230min
Semana
3How 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 leituras, 5 testes
5 leituras
Notes for lesson 5.3.11min
Notes for lesson 5.3.21min
Notes for lesson 5.3.31min
Notes for lesson 5.3.41min
Notes for lesson 5.3.51min
5 exercícios práticos
Practice quiz for lesson 5.3.19min
Practice quiz for lesson 5.3.29min
Practice quiz for lesson 5.3.39min
Practice quiz for lesson 5.3.415min
Quiz for week 330min
Semana
4How 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 leituras, 6 testes
6 leituras
Notes for lesson 5.4.11min
Notes for lesson 5.4.21min
Notes for lesson 5.4.31min
Notes for lesson 5.4.41min
Notes for lesson 5.4.51min
Notes for lesson 5.4.61min
6 exercícios práticos
Practice quiz for lesson 5.4.19min
Practice quiz for lesson 5.4.215min
Practice quiz for lesson 5.4.315min
Practice quiz for lesson 5.4.420min
Practice quiz for lesson 5.4.520min
Quiz for week 440min
Instrutores
Gregory Plett
ProfessorElectrical and Computer Engineering
Sobre 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.
Sobre o Programa de cursos integrados 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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