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
Ce cours fait partie de la Spécialisation Algorithms for Battery Management Systems
Battery Pack Balancing and Power Estimation
proposé par
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
13 heures pour terminer
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 vidéos (Total 79 min), 11 lectures, 6 quiz
7 vidéos
5.1.2: Introduction to battery-pack balancing10 min
5.1.3: How do battery packs become imbalanced?15 min
5.1.4: What are the criteria for specifying a balancing setpoint for a battery pack?13 min
5.1.5: What are the criteria for specifying when to balance a battery pack?13 min
5.1.6: What kinds of circuits can be used for passively balancing a battery pack?16 min
5.1.7: Summary of "Passive balancing methods for battery packs"; what next?2 min
11 lectures
Notes for lesson 5.1.11 min
Frequently Asked Questions5 min
Course Resources5 min
How to Use Discussion Forums5 min
Earn A Certificate5 min
Notes for lesson 5.1.21 min
Notes for lesson 5.1.31 min
Notes for lesson 5.1.41 min
Notes for lesson 5.1.51 min
Notes for lesson 5.1.61 min
Notes for lesson 5.1.71 min
6 exercices pour s'entraîner
Practice quiz for lesson 5.1.29 min
Practice quiz for lesson 5.1.39 min
Practice quiz for lesson 5.1.49 min
Practice quiz for lesson 5.1.59 min
Practice quiz for lesson 5.1.69 min
Quiz for week 130 min
Semaine
23 heures pour terminer
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 vidéos (Total 73 min), 6 lectures, 6 quiz
6 vidéos
5.2.2: How to balance actively using transformer-based circuits7 min
5.2.3: How to balance actively using a shared active bus14 min
5.2.4: Using simulation to show how quickly we must balance a battery pack14 min
5.2.5: Introducing Octave code to simulate balancing: The main program loop21 min
5.2.6: Summary of "Active balancing methods for battery packs"; what next?3 min
6 lectures
Notes for lesson 5.2.11 min
Notes for lesson 5.2.21 min
Notes for lesson 5.2.31 min
Notes for lesson 5.2.41 min
Notes for lesson 5.2.51 min
Notes for lesson 5.2.61 min
6 exercices pour s'entraîner
Practice quiz for lesson 5.2.19 min
Practice quiz for lesson 5.2.29 min
Practice quiz for lesson 5.2.39 min
Practice quiz for lesson 5.2.49 min
Practice quiz for lesson 5.2.515 min
Quiz for week 230 min
Semaine
32 heures pour terminer
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 vidéos (Total 44 min), 5 lectures, 5 quiz
5 vidéos
5.3.2: How to compute available battery power based on cell terminal voltage8 min
5.3.3: How to consider other performance limits when computing available battery power7 min
5.3.4: Introducing Octave code to compute power limits using simplified cell model12 min
5.3.5: Summary of "How to find available battery power using a simplified cell model"; what next?1 min
5 lectures
Notes for lesson 5.3.11 min
Notes for lesson 5.3.21 min
Notes for lesson 5.3.31 min
Notes for lesson 5.3.41 min
Notes for lesson 5.3.51 min
5 exercices pour s'entraîner
Practice quiz for lesson 5.3.19 min
Practice quiz for lesson 5.3.29 min
Practice quiz for lesson 5.3.39 min
Practice quiz for lesson 5.3.415 min
Quiz for week 330 min
Semaine
44 heures pour terminer
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 vidéos (Total 69 min), 6 lectures, 6 quiz
6 vidéos
5.4.2: How to solve for a future battery condition using the bisection algorithm11 min
5.4.3: How to use bisection to estimate available power using comprehensive cell model16 min
5.4.4: Introducing Octave code to compute power limits using comprehensive cell model9 min
5.4.5: Using simulation to compare and contrast different power-estimation methods12 min
5.4.6: Concluding remarks for the specialization6 min
6 lectures
Notes for lesson 5.4.11 min
Notes for lesson 5.4.21 min
Notes for lesson 5.4.31 min
Notes for lesson 5.4.41 min
Notes for lesson 5.4.51 min
Notes for lesson 5.4.61 min
6 exercices pour s'entraîner
Practice quiz for lesson 5.4.19 min
Practice quiz for lesson 5.4.215 min
Practice quiz for lesson 5.4.315 min
Practice quiz for lesson 5.4.420 min
Practice quiz for lesson 5.4.520 min
Quiz for week 440 min
Enseignant
Gregory Plett
ProfessorElectrical and Computer Engineering
À propos de 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.
À propos de la Spécialisation 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.
Foire Aux Questions
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Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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