This course can also be taken for academic credit as ECEA 5733, part of CU Boulder’s Master of Science in Electrical Engineering degree.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Algorithms for Battery Management Systems
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von
University of Colorado Boulder
University of Colorado System
Spezialisierung Algorithms for Battery Management SystemsUniversity of Colorado BoulderÜber diesen Kurs
11.879 kürzliche Aufrufe
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Kurs 4 von 5 in
Stufe „Mittel“
Ca. 23 Stunden zum Abschließen
Englisch
Untertitel: Französisch, Portugiesisch (europäisch), Russisch, Englisch, Spanisch
Was Sie lernen werden
How to implement state-of-health (SOH) estimators for lithium-ion battery cells
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 4 von 5 in
Stufe „Mittel“
Ca. 23 Stunden zum Abschließen
Englisch
Untertitel: Französisch, Portugiesisch (europäisch), Russisch, Englisch, Spanisch
von
University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Science in Electrical Engineering von University of Colorado Boulder.
Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.
Lehrplan - Was Sie in diesem Kurs lernen werden
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
8 Videos (Gesamt 89 min), 13 Lektüren, 7 Quiz
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
7 Videos (Gesamt 68 min), 7 Lektüren, 7 Quiz
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
7 Videos (Gesamt 64 min), 7 Lektüren, 7 Quiz
4 Stunden zum Abschließen
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.
4 Stunden zum Abschließen
6 Videos (Gesamt 70 min), 6 Lektüren, 6 Quiz
Bewertungen
Top-Bewertungen von BATTERY STATE-OF-HEALTH (SOH) ESTIMATION
von AK22. Sep. 2020
It was very new to me, and very interesting stuff. It became even better with the instructor's skill. I would love recommending it to my friends
von AS8. Apr. 2020
A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.
von VK29. Mai 2020
Good course. Nice insight on optimization techniques. Problems and cases studies are really good
von SK23. Aug. 2020
Gave brief overview of SOH and helps in understanding the basic concepts.
Über den Spezialisierung 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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