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 전문 분야
Get Started in Algorithms for Battery Management. Learn how to model lithium-ion battery cells, and how to use those models to manage battery packs
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How the 전문분야 Works
강좌 수강
Coursera 전문 분야는 기술을 완벽하게 습득하는 데 도움이 되는 일련의 강좌입니다. 시작하려면 전문 분야에 직접 등록하거나 강좌를 둘러보고 원하는 강좌를 선택하세요. 하나의 전문 분야에 속하는 강좌에 등록하면 해당 전문 분야 전체에 자동으로 등록됩니다. 단 하나의 강좌만 수료해도 됩니다. — 학습을 일시 중지하거나 언제든 구독을 종료할 수 있습니다. 학습자 대시보드를 방문하여 강좌 등록 상태와 진도를 추적해 보세요.
실습 프로젝트
모든 전문 분야에는 실습 프로젝트가 포함되어 있습니다. 전문 분야를 완료하고 수료증을 받으려면 프로젝트를 성공적으로 마쳐야 합니다. 전문 분야에 별도의 실습 프로젝트 강좌가 포함되어 있는 경우 각 강좌를 완료해야 프로젝트를 시작할 수 있습니다.
수료증 취득
모든 강좌를 마치고 실습 프로젝트를 완료하면 취업할 때나 전문가 네트워크에 진입할 때 제시할 수 있는 수료증을 취득할 수 있습니다.
이 전문분야에는 5개의 강좌가 있습니다.
강좌1
Introduction to battery-management systems
4.7
120개의 평가
This course will provide you with a firm foundation in lithium-ion cell terminology and function and in battery-management-system requirements as needed by the remainder of the specialization. After completing this course, you will be able to:
- List the major functions provided by a battery-management system and state their purpose
- Match battery terminology to a list of definitions
- Identify the major components of a lithium-ion cell and their purpose
- Understand how a battery-management system “measures” current, temperature, and isolation, and how it controls contactors
- Identify electronic components that can provide protection and specify a minimum set of protections needed
- Compute stored energy in a battery pack
- List the manufacturing steps of different types of lithium-ion cells and possible failure modes
강좌2
Equivalent Circuit Cell Model Simulation
4.6
22개의 평가
In this course, you will learn the purpose of each component in an equivalent-circuit model of a lithium-ion battery cell, how to determine their parameter values from lab-test data, and how to use them to simulate cell behaviors under different load profiles. By the end of the course, you will be able to:
- State the purpose for each component in an equivalent-circuit model
- Compute approximate parameter values for a circuit model using data from a simple lab test
- Determine coulombic efficiency of a cell from lab-test data
- Use provided Octave/MATLAB script to compute open-circuit-voltage relationship for a cell from lab-test data
- Use provided Octave/MATLAB script to compute optimized values for dynamic parameters in model
- Simulate an electric vehicle to yield estimates of range and to specify drivetrain components
- Simulate battery packs to understand and predict behaviors when there is cell-to-cell variation in parameter values
강좌3
Battery State-of-Charge (SOC) Estimation
4.6
9개의 평가
In this course, you will learn how to implement different state-of-charge estimation methods and to evaluate their relative merits. By the end of the course, you will be able to:
- Implement simple voltage-based and current-based state-of-charge estimators and understand their limitations
- Explain the purpose of each step in the sequential-probabilistic-inference solution
- Execute provided Octave/MATLAB script for a linear Kalman filter and evaluate results
- Execute provided Octave/MATLAB script for state-of-charge estimation using an extended Kalman filter on lab-test data and evaluate results
- Execute provided Octave/MATLAB script for state-of-charge estimation using an sigma-point Kalman filter on lab-test data and evaluate results
- Implement method to detect and discard faulty voltage-sensor measurements
강좌4
Battery State-of-Health (SOH) Estimation
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)
강좌5
Battery Pack Balancing and Power Estimation
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
강사
Gregory Plett
ProfessorElectrical and Computer Engineering
콜로라도 대학교 정보
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.
자주 묻는 질문
환불 규정은 어떻게 되나요?
하나의 강좌에만 등록할 수 있나요?
네! 시작하려면 관심 있는 강좌 카드를 클릭하여 등록합니다. 강좌를 등록하고 완료하면 공유할 수 있는 인증서를 얻거나 강좌를 청강하여 강좌 자료를 무료로 볼 수 있습니다. 전문 분야 과정에 있는 강좌에 등록하면, 전체 전문 분야에 등록하게 됩니다. 학습자 대시보드에서 진행 사항을 추적할 수 있습니다.
재정 지원을 받을 수 있나요?
해당 강좌를 무료로 수강할 수 있나요?
이 강좌는 100% 온라인으로 진행되나요? 직접 참석해야 하는 수업이 있나요?
이 강좌는 100% 온라인으로 진행되므로 강의실에 직접 참석할 필요가 없습니다. 웹 또는 모바일 장치를 통해 언제 어디서든 강의, 읽기 자료, 과제에 접근할 수 있습니다.
전문 분야를 완료하는 데 얼마나 걸리나요?
The standard version of this specialization is 20 weeks in duration. The honors track requires an additional 4 weeks of study.
What background knowledge is necessary?
This is a graduate-level specialization that assumes that learners already hold a technical undergraduate degree: a Bachelor's degree in Electrical Engineering, Computer Engineering, or Mechanical Engineering or a Bachelor's degree in a closely related engineering discipline plus undergraduate-level competency in the following areas: Math (differential and integral calculus, linear algebra, and differential equations), Science (calculus-based physics and general chemistry), and Engineering (linear circuits, electronics, and linear systems)
Do I need to take the courses in a specific order?
The courses are designed to be taken in order, from Course 1 through Course 5. Course 1 gives a broad overview, background concepts, and context for the others; Course 2 is a strong prerequisite for the remaining courses since it describes the mathematical and programming frameworks that will be used; Course 3 includes topics in random variables that are important for Course 4. Course 5 is the only exception, and may be taken any time after completing Course 2.
전문 분야를 완료하면 대학 학점을 받을 수 있나요?
No.
What will I be able to do upon completing the Specialization?
After completing the specialization, you will be able to: use laboratory data to create mathematical models of battery cells, and use these models to implement state-of-charge, state-of-health, available power (state-of-function), available energy, and balancing algorithms.
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