À propos de ce cours
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Niveau intermédiaire

Approx. 17 heures pour terminer

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Sous-titres : Anglais

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau intermédiaire

Approx. 17 heures pour terminer

Recommandé : 14 hours/week...

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
4 heures pour terminer

How does lithium-ion cell health degrade?

As battery cells age, their total capacities generally decrease and their resistances generally increase. This week, you will learn WHY this happens. You will learn about the specific physical and chemical mechanisms that cause degradation to lithium-ion battery cells. You will also learn why it is relatively simple to estimate and track changes to resistance, but why it is difficult to track changes to total capacity accurately....
8 vidéos (Total 89 min), 12 lectures, 7 quiz
8 vidéos
4.1.2: What changes as a cell ages?16 min
4.1.3: Negative-electrode aging processes at particle surface16 min
4.1.4: Negative-electrode aging processes in bulk and composite electrode9 min
4.1.5: Positive-electrode aging processes10 min
4.1.6: Sensitivity of cell voltage to changes in equivalent series resistance (ESR)17 min
4.1.7: Sensitivity of cell voltage to changes in cell total capacity9 min
4.1.8: Summary of "How does lithium-ion cell health degrade?"; what next?2 min
12 lectures
Notes for lesson 4.1.11 min
Frequently Asked Questions5 min
Course Resources5 min
How to Use Discussion Forums5 min
Earn a Course Certificate5 min
Notes for lesson 4.1.21 min
Notes for lesson 4.1.31 min
Notes for lesson 4.1.41 min
Notes for lesson 4.1.51 min
Notes for lesson 4.1.61 min
Notes for lesson 4.1.71 min
Notes for lesson 4.1.81 min
7 exercices pour s'entraîner
Practice quiz for lesson 4.1.29 min
Practice quiz for lesson 4.1.39 min
Practice quiz for lesson 4.1.49 min
Practice quiz for lesson 4.1.59 min
Practice quiz for lesson 4.1.615 min
Practice quiz for lesson 4.1.79 min
Quiz for week 145 min
Semaine
2
4 heures pour terminer

Total-least-squares battery-cell capacity estimation

Total capacity is often estimated using ordinary-least-squares (OLS) methods. This week, you will learn that this is a fundamentally incorrect approach, and will learn that a total-least-squares (TLS) method should be used instead. You will learn how to derive a weighted OLS solution, to use as a benchmark, and how to derive a weighted TLS solution also....
7 vidéos (Total 68 min), 7 lectures, 7 quiz
7 vidéos
4.2.2: How to find the ordinary-least-squares solution as a benchmark9 min
4.2.3: Making the ordinary-least-squares solution computationally efficient12 min
4.2.4: Setting up weighted total-least-squares solution11 min
4.2.5: Finding the solution to a weighted total-least-squares problem10 min
4.2.6: Confidence intervals on least-squares solutions11 min
4.2.7: Summary of "Total-least-squares battery-cell capacity estimation"; what next?2 min
7 lectures
Notes for lesson 4.2.11 min
Notes for lesson 4.2.21 min
Notes for lesson 4.2.31 min
Notes for lesson 4.2.41 min
Notes for lesson 4.2.51 min
Notes for lesson 4.2.61 min
Notes for lesson 4.2.71 min
7 exercices pour s'entraîner
Practice quiz for lesson 4.2.19 min
Practice quiz for lesson 4.2.215 min
Practice quiz for lesson 4.2.315 min
Practice quiz for lesson 4.2.49 min
Practice quiz for lesson 4.2.515 min
Practice quiz for lesson 4.2.615 min
Quiz for week 245 min
Semaine
3
4 heures pour terminer

Simplified total-least-squares battery-cell capacity estimates

Unfortunately, the weighted TLS solution you learned in week 2 is not well suited for efficient computation on an embedded system like a BMS. As an intermediate step toward finding an efficient weighted TLS method, you will first learn a proportionally weighted TLS method this week. You will then learn how to generalize this to an "approximate weighted TLS" (AWTLS) method, which gives good estimates, and is feasible to implement on a BMS....
7 vidéos (Total 64 min), 7 lectures, 7 quiz
7 vidéos
4.3.2: Making simplified solution computationally efficient6 min
4.3.3: Defining geometry for approximate full solution to weighted total least squares12 min
4.3.4: Finding appropriate cost function for approximate full solution to WTLS problem8 min
4.3.5: Finding solution to the AWTLS problem10 min
4.3.6: Adding fading memory8 min
4.3.7: Summary of "Simplified total-least-squares battery-cell capacity estimates"; what next?4 min
7 lectures
Notes for lesson 4.3.11 min
Notes for lesson 4.3.21 min
Notes for lesson 4.3.31 min
Notes for lesson 4.3.41 min
Notes for lesson 4.3.51 min
Notes for lesson 4.3.61 min
Notes for lesson 4.3.71 min
7 exercices pour s'entraîner
Practice quiz for lesson 4.3.115 min
Practice quiz for lesson 4.3.220 min
Practice quiz for lesson 4.3.39 min
Practice quiz for lesson 4.3.49 min
Practice quiz for lesson 4.3.515 min
Practice quiz for lesson 4.3.615 min
Quiz for week 345 min
Semaine
4
4 heures pour terminer

How to write code for the different total-capacity estimators

So far this course, you have learned a number of methods for estimating total capacity. This week, you will learn how to implement those methods in Octave code. You will also explore different simulation scenarios to benchmark how well each method works, in comparison with the others. The scenarios are representative of hybrid-electric-vehicle (HEV) and battery-electric-vehicle (BEV) applications, but the principles learned can be extrapolated to other similar application domains....
6 vidéos (Total 70 min), 6 lectures, 6 quiz
6 vidéos
4.4.2: Demonstrating Octave code for HEV: Scenario 121 min
4.4.3: Demonstrating Octave code for HEV: Scenarios 2–37 min
4.4.4: Demonstrating Octave code for BEV: Scenario 16 min
4.4.5: Demonstrating Octave code for BEV: Scenarios 2–310 min
4.4.6: Summary of "How to write code for the different total-capacity estimators"; what next?9 min
6 lectures
Notes for lesson 4.4.11 min
Notes for lesson 4.4.21 min
Notes for lesson 4.4.31 min
Notes for lesson 4.4.41 min
Notes for lesson 4.4.51 min
Notes for lesson 4.4.61 min
6 exercices pour s'entraîner
Practice quiz for lesson 4.4.115 min
Practice quiz for lesson 4.4.215 min
Practice quiz for lesson 4.4.315 min
Practice quiz for lesson 4.4.415 min
Practice quiz for lesson 4.4.515 min
Quiz for week 445 min
Semaine
5
3 heures pour terminer

A Kalman-filter approach to total capacity estimation

In the third course of the specialization, you learned how to use extended Kalman filters (EKFs) and sigma-point Kalman filters (SPKFs) to estimate the state of a battery cell. In this honors week, you will learn how to extend those concepts to apply EKF and SPKF to estimating the parameters of a battery-cell model if the state is known, and also how to simultaneously estimate both the state and parameters of a cell model....
6 vidéos (Total 54 min), 6 lectures, 4 quiz
6 vidéos
4.5.2: Deriving EKF method for parameter estimation8 min
4.5.3: How to estimate states and parameters at the same time9 min
4.5.4: Defining the steps for EKF and SPFK joint and dual estimation4 min
4.5.5: Addressing issues of robustness and speed12 min
4.5.6: Summary of "A Kalman-filter approach to total capacity estimation"; what next?2 min
6 lectures
Notes for lesson 4.5.11 min
Notes for lesson 4.5.21 min
Notes for lesson 4.5.31 min
Notes for lesson 4.5.41 min
Notes for lesson 4.5.51 min
Notes for lesson 4.5.61 min
4 exercices pour s'entraîner
Quiz for lesson 4.5.115 min
Quiz for lesson 4.5.215 min
Quiz for lessons 4.5.3 and 4.5.412 min
Quiz for lesson 4.5.525 min
Semaine
6
4 heures pour terminer

Capstone project

You have learned several different total-capacity estimation methods. Some of these methods work better than others in general, but any method is only as good as the data you give it. In this project, you will explore a different way to determine the "x" and "y" data you use as input to the total-capacity estimation methods....
1 quiz

Enseignant

Gregory Plett

Professor
Electrical 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....
Algorithms for Battery Management Systems

Foire Aux Questions

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