Hello, my name is Gregory Plett. And it's my very great pleasure to welcome you to this Coursera specialization on Algorithms for Battery Management Systems. As you know, batteries power just about everything in our modern lives. Batteries power portable electronics like mobile phones, and laptop computers, and fitness watches, and music players, and power tools, and many other consumer electronic devices. Batteries are beginning to power our vehicles as well, from mild hybrid electric vehicles to plug-in hybrid electric vehicles. All the way up to full scale battery electric vehicles. And batteries are going to power the future electric grid with frequency regulation, and grid storage, and grid back up, and other similar applications. Batteries need to be managed properly by a battery management system that comprises specialized electronics and specialized software that are co-designed in order to accomplish a number of very important goals. First, the battery management system needs to make sure that it protects the human users of the application that is being powered by the battery. Second, it needs to make sure that it protects the battery pack itself from any kind of damage and abuse, because the battery is an extremely expensive investment in many cases. Third, because the battery is an expensive investment, the battery management system needs to maximize the performance that can be squeezed out of the battery system. Because we don't want to waste anything we have paid money for. And finally, the battery management system needs to make sure that it maximizes the life that we can get out of the battery system. Again, because of the significant investment that was made in it. Algorithms are computer methods, computer code that are designed to accomplish specific tasks and specific goals. And therefore this Coursera specialization is all about algorithms or computer methods that can be implemented in a battery management system, having specialized electronics that enable this implementation. These algorithms are designed to protect the user, to protect the battery pack and to optimize a trade-off between performance and life of the battery system itself. You're going to learn about many battery management topics in this specialization, spread out over five individual courses. Each course has its own icon to help you recognize where you are in the process. The first course is about functional requirements that must be satisfied by a battery management system on its requirements for electronics and its software components. And understanding generally how battery cells work, and how they're made, and how they fail. The focus of this specialization is going to be on lithium-ion battery cells, but some of what the first course teaches is more general than that. The second course dives more deeply into making mathematical models or sets of equations that describe lithium-ion battery cells from an input to output perspective. Mapping the electrical current input to the cell and the voltage response of the cell as its output. And then we're going to eventually use these models in some of the algorithms that will be developed further on in this specialization. And in particular, in the second course you will learn about equivalent circuit models, which are state of the art right now. You will see how to create the models, how to collect data in a laboratory and perform processing to find the parameter values of the models to describe a specific cell of interest. And then how to use the models to simulate behaviors of individual cells as well as large battery packs. Third, you will learn about a topic known as state estimation and specifically at state-of-charge estimation for battery systems. This estimate provides a kind of a fuel gauge that allows us to compute how much energy remains in a cell that can be used to perform work. Our focus is going to be on advanced estimators based on common filtering theory. Learning how these methods work starting with very basic principles and ending up with MATLAB or Octave programming code that implements the estimators. Fourth, you will learn about how to estimate battery cell state-of-health. Battery cells lose their energy storage capacity and power delivery capacity as they age. And we need to be able to estimate state-of-health to know whether the battery is brand new or if it's aging, or if it's aged to the point where it needs to be replace. And also to know how best to use the battery at whatever stage of life it might presently be. And in the fifth specialization course, you will learn about two main topics. One is on balancing or equalization and the other is on estimating power limits. Balancing has to do with keeping all of the battery cells in the battery pack at a uniformly operational state. Even though the characteristics of each individual cell in the battery pack may be slightly different. Power limits estimates tell me how much power I can safely get out of the battery packet at this particular point in time without causing life hazards or safety hazards. Additionally, there's an honors track available in this specialization. So if you have a really keen interest, you can gain greater insight and greater skills by watching the video lessons and by taking all of the assignments in the honors track. Since you are new to this specialization, you may wonder if your background has prepared you to be successful. So on this slide, I've listed some of the prerequisites that you should have. You are a good fit for this specialization if you already have a bachelor's degree in an engineering discipline such as electrical engineering, or computer engineering, or mechanical engineering. Or perhaps you hold a bachelor's degree in a related field and you have a background prerequisite knowledge from other forms of study. In particular, what topics do you need to know? Well, you're going to need to know some math. This specialization, I would consider to be at a graduate level. So you need to have an undergraduate level competence in finding derivatives and integrals of expressions, so calculus. And performing operations with vectors and matrices, so linear algebra, but the focus will be on the mechanics of linear algebra. Being able to perform the computations and not so much on the detailed theory of linear algebra, talking about proofs, and so forth. That's not our concern as much in this specialisation. You're also going to need to have some understanding of basic differential equations. You also need some background on other engineering topics, particularly in what is normally called linear circuits. So, specifically, you need to understand how to model resistors and capacitors and voltage sources, and how they interact with each other if they're in a circuit that combines multiple elements. Because these are going to be used to help us describe how a battery cell operates. And finally, you're going to need some computer programming skills. This specialization uses Octave as its main programming environment. If you're not familiar with Octave, it's an open-source free alternative to a proprietary programming environment called MATLAB, which is marketed by the MathWorks. If you've used either MATLAB or Octave in the past, you should be very well prepared. If you have not, then there are other Coursera specializations available that can help you to learn these skills before you come to this one. If, however, you are very proficient in programming in some other language like, perhaps, C, then the details of how MATLAB and Octave differ from C are things that I expect you can pick up quite rapidly. But if you have no real programming background at all, then I would discourage you from taking this course because, after all, this specialization is about algorithms or computer methods. And so we will be designing these over the five courses. If you are still unsure whether you have the right depth of knowledge, I've provided a prerequisite quiz this week that you can take. If you do well on the quiz, then you should have the background skills required to succeed in this specialization also. There's an optional set of textbooks that you might decide to purchase if you wish to gain deeper insights or to have a permanent reference. I am the author of these books. And I authored them after having been a researcher in the field and a practitioner in the field of battery modeling and battery management for more than 15 years. And they summarize what I consider to be the state of the art in the field. These textbooks are not required. It's possible to succeed without these textbooks. But if you desire to purchase them, then they are available from the Artech House Publishers website, and also many other online book sellers sell them as well. In this specialization, we will spend most of our time and focus on the topics covered by the second book, the green one on the right. Which talks about equivalent circuit methods for battery management systems. You're going to learn the material covered in six out of seven of the chapters in the book in this specialization. The blue book on the left might be a good reference for you, but it's not something that we will be using every day in this specialization. However, we still will cover two of the seven chapters in that book as well, the first two background chapters. So again, welcome. I'm very glad you're taking this specialization and I believe you're going to learn a lot of very important things. You're going to learn valuable state of the art skills in the primary algorithm tasks required by a battery management system. And moreover, you're going to learn how to apply these skills by actually implementing battery management algorithms in Octave code for different battery application domains. So welcome and best wishes.
