需要一些相關領域經驗。需要一些相關經驗。
2,883 人已註冊
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關於此 專項課程
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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.
應用的學習項目
Learners will start with supplied code templates (in the Octave/MATLAB language) to build their own code to simulate lithium-ion battery cells and packs, and to estimate battery cell state-of-charge, state-of-health (capacity and resistance), remaining energy, and available power.
學生職業成果
29%
完成此 專項課程 後開始了新的職業。
14%
加薪或升職。
學生職業成果
29%
完成此 專項課程 後開始了新的職業。
14%
加薪或升職。
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為4 個月
建議 11 小時/週
英語（English）
字幕：英語（English）
專項課程的運作方式
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實踐項目
每個專項課程都包括實踐項目。您需要成功完成這個（些）項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程，則需要在開始之前完成其他所有課程。
獲得證書
在結束每門課程並完成實踐項目之後，您會獲得一個證書，您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。
此專項課程包含 5 門課程
Introduction to battery-management systems
367 個評分
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:
Equivalent Circuit Cell Model Simulation
57 個評分
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:
Battery State-of-Charge (SOC) Estimation
40 個評分
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:
Battery State-of-Health (SOH) Estimation
22 個評分
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:
提供方
科罗拉多大学系统
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.
審閱
4.8
來自ALGORITHMS FOR BATTERY MANAGEMENT SYSTEMS的熱門評論
由 AC 提供Jan 12, 2020
The introductory concepts covered were excellent and motivates me to take further courses in the specialization!
由 RS 提供Jan 23, 2019
Very good course for the beginners. Mr. Plett explains the concepts so clearly and his teaching style makes the subject more interesting. This course is very useful to those who are interested in BMS.
由 MM 提供Nov 26, 2018
It's a good course with excellent illustration, it just needs more examples to add more valid ways of calculations. Even thou it was a very challenging course. I enjoyed!
由 ME 提供Jan 7, 2020
The course was well planned and organised! There is flexibility in the course deadline which is appreciable and suitable for students, Working professionals, faculties.
由 SC 提供Apr 14, 2019
This course is really interesting .This includes the basic information of battery working which was very helpful for me as I am from Mechanical Engineering Background
由 MP 提供Oct 3, 2019
Excellent introduction. Although, I have worked extensively worked on batteries I could still find lot of information which we generally tend to neglect.
由 KE 提供Nov 14, 2019
This is the best online course I’ve ever taken. The professor handling this course is a very talented teacher. Very good course. I highly recommend this
由 KY 提供Jul 22, 2019
I think, after the test passed, the answer should be prepared for students. By the way, It was a great opportunity for learning the function of BMS
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有助学金吗？
我可以免费学习课程吗？
此课程是 100% 在线学习吗？是否需要现场参加课程？
此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。
完成专项课程需要多长时间？
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.
完成专项课程后我会获得大学学分吗？
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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