This course can also be taken for academic credit as ECEA 5733, part of CU Boulder’s Master of Science in Electrical Engineering degree.
Este curso forma parte de Programa especializado: Algorithms for Battery Management Systems
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ofrecido por
Universidad de Colorado en Boulder
Sistema Universitario de Colorado
Programa especializado: Algorithms for Battery Management SystemsUniversidad de Colorado en BoulderAcerca de este Curso
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Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 23 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
Qué aprenderás
How to implement state-of-health (SOH) estimators for lithium-ion battery cells
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 23 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad de Colorado en 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.
Sistema Universitario de Colorado
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.
Comienza a trabajar para obtener tu maestría
Este curso es parte del Master of Science in Electrical Engineering completamente en línea de Universidad de Colorado en Boulder.
Si te aceptan en el programa completo, tus cursos cuentan para tu título de grado.
Programa - Qué aprenderás en este curso
4 horas para completar
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 horas para completar
8 videos (Total 89 minutos), 13 lecturas, 7 cuestionarios
4 horas para completar
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 horas para completar
7 videos (Total 68 minutos), 7 lecturas, 7 cuestionarios
4 horas para completar
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 horas para completar
7 videos (Total 64 minutos), 7 lecturas, 7 cuestionarios
4 horas para completar
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 horas para completar
6 videos (Total 70 minutos), 6 lecturas, 6 cuestionarios
Reseñas
Principales reseñas sobre BATTERY STATE-OF-HEALTH (SOH) ESTIMATION
por AK22 de sep. de 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
por AS8 de abr. de 2020
A detailed course on battery capacity estimation, which covers overall perspectives, and complications in the SOH estimation of the battery.
por VK29 de may. de 2020
Good course. Nice insight on optimization techniques. Problems and cases studies are really good
por SK23 de ago. de 2020
Gave brief overview of SOH and helps in understanding the basic concepts.
Acerca de Programa especializado: 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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