The advent of lithium ion batteries has brought a significant shift in the area of large format battery systems. Previously limited to heavy and bulky lead-acid storage batteries, large format batteries were used only where absolutely necessary as a means of energy storage. The improved energy density, cycle life, power capability, and durability of lithium ion cells has given us electric and hybrid vehicles with meaningful driving range and performance, grid-tied energy storage systems for integration of renewable energy and load leveling, backup power systems and other applications. This book discusses battery management system (BMS) technology for large format lithium-ion battery packs from a systems perspective. This resource covers the future of BMS, giving us new ways to generate, use, and store energy, and free us from the perils of non-renewable energy sources. This book provides a full update on BMS technology, covering software, hardware, integration, testing, and safety.

This timely book provides you with a solid understanding of battery management systems (BMS) in large Li-Ion battery packs, describing the important technical challenges in this field and exploring the most effective solutions. You find in-depth discussions on BMS topologies, functions, and complexities, helping you determine which permutation is right for your application. Packed with numerous graphics, tables, and images, the book explains the OC whysOCO and OC howsOCO of Li-Ion BMS design, installation, configuration and troubleshooting. This hands-on resource includes an unbiased description and comparison of all the off-the-shelf Li-Ion BMSs available today. Moreover, it explains how using the correct one for a given application can help to get a Li-Ion pack up and running in little time at low cost."

Battery Management Systems - Design by Modelling describes the design of Battery Management Systems (BMS) with the aid of simulation methods. The basic tasks of BMS are to ensure optimum use of the energy stored in the battery (pack) that powers a portable device and to prevent damage inflicted on the battery (pack). This becomes increasingly important due to the larger power consumption associated with added features to portable devices on the one hand and the demand for longer run times on the other hand. In addition to explaining the general principles of BMS tasks such as charging algorithms and State-of-Charge (SoC) indication methods, the book also covers real-life examples of BMS functionality of practical portable devices such as shavers and cellular phones. Simulations offer the advantage over measurements that less time is needed to gain knowledge of a battery's behaviour in interaction with other parts in a portable device under a wide variety of conditions. This knowledge can be used to improve the design of a BMS, even before a prototype of the portable device has been built. The battery is the central part of a BMS and good simulation models that can be used to improve the BMS design were previously unavailable. Therefore, a large part of the book is devoted to the construction of simulation models for rechargeable batteries. With the aid of several illustrations it is shown that design improvements can indeed be realized with the presented battery models. Examples include an improved charging algorithm that was elaborated in simulations and verified in practice and a new SoC indication system that was developed showing promising results. The contents of Battery Management Systems - Design by Modelling is based on years of research performed at the Philips Research Laboratories. The combination of basic and detailed descriptions of battery behaviour both in chemical and electrical terms makes this book truly multidisciplinary. It can therefore be read both by people with an (electro)chemical and an electrical engineering background.

Addresses the methodology and theoretical foundation of battery manufacturing, service and management systems (BM2S2), and discusses the issues and challenges in these areas This book brings together experts in the field to highlight the cutting edge research advances in BM2S2 and to promote an innovative integrated research framework responding to the challenges. There are three major parts included in this book: manufacturing, service, and management. The first part focuses on battery manufacturing systems, including modeling, analysis, design and control, as well as economic and risk analyses. The second part focuses on information technology’s impact on service systems, such as data-driven reliability modeling, failure prognosis, and service decision making methodologies for battery services. The third part addresses battery management systems (BMS) for control and optimization of battery cells, operations, and hybrid storage systems to ensure overall performance and safety, as well as EV management. The contributors consist of experts from universities, industry research centers, and government agency. In addition, this book: Provides comprehensive overviews of lithium-ion battery and battery electrical vehicle manufacturing, as well as economic returns and government support Introduces integrated models for quality propagation and productivity improvement, as well as indicators for bottleneck identification and mitigation in battery manufacturing Covers models and diagnosis algorithms for battery SOC and SOH estimation, data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH Presents mathematical models and novel structure of battery equalizers in battery management systems (BMS) Reviews the state of the art of battery, supercapacitor, and battery-supercapacitor hybrid energy storage systems (HESSs) for advanced electric vehicle applications Advances in Battery Manufacturing, Services, and Management Systems is written for researchers and engineers working on battery manufacturing, service, operations, logistics, and management. It can also serve as a reference for senior undergraduate and graduate students interested in BM2S2.

This book introduces several battery management problems and provides solutions using model-based approaches. It provides detailed coverage of battery management problems, including battery impedance estimation, battery capacity estimation, state of charge estimation, state of health estimation, battery thermal management, and optimal charging algorithms. The book introduces important battery management problems in a modularized fashion, decoupling each battery management problem from others as much as possible, allowing you to focus on understanding a particular topic rather than having to understand all aspects of a battery management system. You will get the necessary background to understand, implement and improve battery fuel gauges in electric vehicles, and general state of health of the battery; use proven models and algorithms to estimate the thermal properties of a battery; and know the basics of smart battery charger design. You will also be equipped to accurately estimate battery features of vehicles, such as state of charge, expected charging time, and state of health, to make customized charging waveforms for each vehicle. The book teaches you how to create simulation environments to test and validate algorithms against model uncertainty and measurement noise. In addition, the importance of benchmarking battery management algorithms is covered, and several bench marking metrics are presented. Included MATLAB codes give you an easy way to test the algorithms using realistic data and to develop and test alternative solutions. This is a useful and timely guide for battery engineers at all levels, as well as research scientists and advanced students working in this robust and rapidly advancing area.

State-Of-The-Art applications of equivalent-circuit methods as they pertain to solving problems in battery management and control.

This new resource provides you with an introduction to battery design and test considerations for large-scale automotive, aerospace, and grid applications. It details the logistics of designing a professional, large, Lithium-ion battery pack, primarily for the automotive industry, but also for non-automotive applications. Topics such as thermal management for such high-energy and high-power units are covered extensively, including detailed design examples. Every aspect of battery design and analysis is presented from a hands-on perspective. The authors work extensively with engineers in the field and this book is a direct response to frequently-received queries. With the authors’ unique expertise in areas such as battery thermal evaluation and design, physics-based modeling, and life and reliability assessment and prediction, this book is sure to provide you with essential, practical information on understanding, designing, and building large format Lithium-ion battery management systems.

This comprehensive, two-volume resource provides a thorough introduction to lithium ion (Li-ion) technology. Readers get a hands-on understanding of Li-ion technology, are guided through the design and assembly of a battery, through deployment, configuration and testing. The book covers dozens of applications, with solutions for each application provided. Volume One focuses on the Li-ion cell and its types, formats, and chemistries. Cell arrangements and issues, including series (balance) and parallel (fusing, inrush current) are also discussed. Li-ion Battery Management Systems are explored, focusing on types and topologies, functions, and selection. Battery design, assembly, deployment, troubleshooting and repair are also discussed, along with modular batteries, split batteries and battery arrays. Written by a prominent expert in the field and packed with over 500 illustrations, these volumes contain solutions to practical problems, making it useful for both the novice and experienced practitioners.

Large-scale battery packs are needed in hybrid and electric vehicles, utilities grid backup and storage, and frequency-regulation applications. In order to maximize battery-pack safety, longevity, and performance, it is important to understand how battery cells work. This first of its kind new resource focuses on developing a mathematical understanding of how electrochemical (battery) cells work, both internally and externally. This comprehensive resource derives physics-based micro-scale model equations, then continuum-scale model equations, and finally reduced-order model equations. This book describes the commonly used equivalent-circuit type battery model and develops equations for superior physics-based models of lithium-ion cells at different length scales. This resource also presents a breakthrough technology called the “discrete-time realization algorithm” that automatically converts physics-based models into high-fidelity approximate reduced-order models.

This book -- the third and final volume in a series describing battery-management systems – shows you how to use physics-based models of battery cells in a computationally efficient way for optimal battery-pack management and control to maximize battery-pack performance and extend life. It covers the foundations of electrochemical model-based battery management system while introducing and teaching the state of the art in physics-based methods for battery management. Building upon the content in volumes I and II, the book helps you identify parameter values for physics-based models of a commercial lithium-ion battery cell without requiring cell teardown; shows you how to estimate the internal electrochemical state of all cells in a battery pack in a computationally efficient way during operation using these physics-based models; demonstrates the use the models plus state estimates in a battery management system to optimize fast-charge of battery packs to minimize charge time while also maximizing battery service life; and takes you step-by-step through the use models to optimize the instantaneous power that can be demanded from the battery pack while also maximizing battery service life. The book also demonstrates how to overcome the primary roadblocks to implementing physics-based method for battery management: the computational-complexity roadblock, the parameter-identification roadblock, and the control-optimization roadblock. It also uncovers the fundamental flaw in all present “state of art” methods and shows you why all BMS based on equivalent-circuit models must be designed with over-conservative assumptions. This is a strong resource for battery engineers, chemists, researchers, and educators who are interested in advanced battery management systems and strategies based on the best available understanding of how battery cells operate.