Este curso forma parte de Programa Especializado - Algorithms for Battery Management Systems

Gregory Plett

ofrecido por

Universidad de Colorado en Boulder

Sistema Universitario de Colorado

Parte del título Master of Science in Electrical Engineering

Más información

Programa Especializado - Algorithms for Battery Management SystemsUniversidad de Colorado en Boulder

Acerca de este Curso

17,534 vistas recientes

This course can also be taken for academic credit as ECEA 5733, part of CU Boulder’s Master of Science in Electrical Engineering degree.
In this course, you will learn how to implement different state-of-health estimation methods and to evaluate their relative merits. By the end of the course, you will be able to:
-	Identify the primary degradation mechanisms that occur in lithium-ion cells and understand how they work
-	Execute provided Octave/MATLAB script to estimate total capacity using WLS, WTLS, and AWTLS methods and lab-test data, and to evaluate results
-	Compute confidence intervals on total-capacity estimates 
-	Compute estimates of a cell’s equivalent-series resistance using lab-test data
-	Specify the tradeoffs between joint and dual estimation of state and parameters, and steps that must be taken to ensure robust estimates (honors)

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Curso 4 de 5 en

Programa Especializado - Algorithms for Battery Management Systems

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 23 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Qué aprenderás

How to implement state-of-health (SOH) estimators for lithium-ion battery cells

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 4 de 5 en

Programa Especializado - Algorithms for Battery Management Systems

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 23 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Instructor

Calificación del instructor

5/5 (7 calificaciones)

Gregory Plett

Professor

Electrical and Computer Engineering

24,978 alumnos

5 cursos

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 eres aceptado en el programa completo, tus cursos cuentan para tu título.

Más información

Programa - Qué aprenderás en este curso

Semana

Semana 1

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), 12 lecturas, 7 cuestionarios

8 videos

4.1.1: Welcome to the course!7m

4.1.2: What changes as a cell ages?16m

4.1.3: Negative-electrode aging processes at particle surface16m

4.1.4: Negative-electrode aging processes in bulk and composite electrode9m

4.1.5: Positive-electrode aging processes10m

4.1.6: Sensitivity of cell voltage to changes in equivalent series resistance (ESR)17m

4.1.7: Sensitivity of cell voltage to changes in cell total capacity9m

4.1.8: Summary of "How does lithium-ion cell health degrade?"; what next?2m

12 lecturas

Notes for lesson 4.1.11m

Frequently asked questions5m

Course resources5m

How to use discussion forums5m

Earn a course certificate5m

Notes for lesson 4.1.21m

Notes for lesson 4.1.31m

Notes for lesson 4.1.41m

Notes for lesson 4.1.51m

Notes for lesson 4.1.61m

Notes for lesson 4.1.71m

Notes for lesson 4.1.81m

7 ejercicios de práctica

Practice quiz for lesson 4.1.29m

Practice quiz for lesson 4.1.39m

Practice quiz for lesson 4.1.49m

Practice quiz for lesson 4.1.59m

Practice quiz for lesson 4.1.615m

Practice quiz for lesson 4.1.79m

Quiz for week 145m

Semana

Semana 2

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

7 videos

4.2.1: What’s wrong with using ordinary least squares to estimate total capacity?9m

4.2.2: How to find the ordinary-least-squares solution as a benchmark9m

4.2.3: Making the ordinary-least-squares solution computationally efficient12m

4.2.4: Setting up weighted total-least-squares solution11m

4.2.5: Finding the solution to a weighted total-least-squares problem10m

4.2.6: Confidence intervals on least-squares solutions11m

4.2.7: Summary of "Total-least-squares battery-cell capacity estimation"; what next?2m

7 lecturas

Notes for lesson 4.2.11m

Notes for lesson 4.2.21m

Notes for lesson 4.2.31m

Notes for lesson 4.2.41m

Notes for lesson 4.2.51m

Notes for lesson 4.2.61m

Notes for lesson 4.2.71m

7 ejercicios de práctica

Practice quiz for lesson 4.2.19m

Practice quiz for lesson 4.2.215m

Practice quiz for lesson 4.2.315m

Practice quiz for lesson 4.2.49m

Practice quiz for lesson 4.2.515m

Practice quiz for lesson 4.2.615m

Quiz for week 245m

Semana

Semana 3

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

7 videos

4.3.1: Simplifying the total-least-squares solution for cases having proportional uncertainties13m

4.3.2: Making simplified solution computationally efficient6m

4.3.3: Defining geometry for approximate full solution to weighted total least squares12m

4.3.4: Finding appropriate cost function for approximate full solution to WTLS problem8m

4.3.5: Finding solution to the AWTLS problem10m

4.3.6: Adding fading memory8m

4.3.7: Summary of "Simplified total-least-squares battery-cell capacity estimates"; what next?4m

7 lecturas

Notes for lesson 4.3.11m

Notes for lesson 4.3.21m

Notes for lesson 4.3.31m

Notes for lesson 4.3.41m

Notes for lesson 4.3.51m

Notes for lesson 4.3.61m

Notes for lesson 4.3.71m

7 ejercicios de práctica

Practice quiz for lesson 4.3.115m

Practice quiz for lesson 4.3.220m

Practice quiz for lesson 4.3.39m

Practice quiz for lesson 4.3.49m

Practice quiz for lesson 4.3.515m

Practice quiz for lesson 4.3.615m

Quiz for week 345m

Semana

Semana 4

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

6 videos

4.4.1: Introducing Octave code to estimate cell total capacity13m

4.4.2: Demonstrating Octave code for HEV: Scenario 121m

4.4.3: Demonstrating Octave code for HEV: Scenarios 2–37m

4.4.4: Demonstrating Octave code for BEV: Scenario 16m

4.4.5: Demonstrating Octave code for BEV: Scenarios 2–310m

4.4.6: Summary of "How to write code for the different total-capacity estimators"; what next?9m

6 lecturas

Notes for lesson 4.4.11m

Notes for lesson 4.4.21m

Notes for lesson 4.4.31m

Notes for lesson 4.4.41m

Notes for lesson 4.4.51m

Notes for lesson 4.4.61m

6 ejercicios de práctica

Practice quiz for lesson 4.4.115m

Practice quiz for lesson 4.4.215m

Practice quiz for lesson 4.4.315m

Practice quiz for lesson 4.4.415m

Practice quiz for lesson 4.4.515m

Quiz for week 445m

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.

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
¿Recibiré crédito universitario por completar el Curso?
Este Curso no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del curso para obtener crédito. Consulta con tu institución para obtener más información. Los Títulos en línea y los Certificados Mastertrack™ de Coursera brindan la oportunidad de obtener créditos universitarios.

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Battery State-of-Health (SOH) Estimation