Electrochemical Model-based State of Charge and State of Health Estimation of Lithium-ion Batteries

Electrochemical Model-based State of Charge and State of Health Estimation of Lithium-ion Batteries PDF Author: Alexander Paul Bartlett
Publisher:
ISBN:
Category :
Languages : en
Pages : 251

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Book Description
Vehicle electrification continues to be a key topic of interest for automotive manufacturers, in an effort to reduce the usage of fossil fuel energy and improve vehicle efficiency. Lithium-ion batteries are currently the technology of choice for hybrid and electric vehicles due to their decreasing cost and improved power and energy density over traditional lead-acid or nickel-metal-hydride batteries. In particular, batteries with composite electrodes have seen increased use in automotive applications due to their ability to balance energy density, power density, and cost by adjusting the amount of each material within the electrode. However, this improved performance introduces new challenges to ensure the battery pack operates safely, reliably, and durably. The vehicle's battery management system (BMS) is designed to meet these challenges, in part, by estimating the battery state of charge (SOC) and state of health (SOH). Knowledge of SOC allows the BMS to predict the available instantaneous power while ensuring the battery is operating within safe limits. As batteries age, they lose capacity and the ability to deliver power. Therefore, tracking the battery SOH is necessary to maintain accurate estimates of SOC and power throughout the battery life and give an accurate miles-to-empty metric to the driver.

Electrochemical Model-based State of Charge and State of Health Estimation of Lithium-ion Batteries

Electrochemical Model-based State of Charge and State of Health Estimation of Lithium-ion Batteries PDF Author: Alexander Paul Bartlett
Publisher:
ISBN:
Category :
Languages : en
Pages : 251

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Book Description
Vehicle electrification continues to be a key topic of interest for automotive manufacturers, in an effort to reduce the usage of fossil fuel energy and improve vehicle efficiency. Lithium-ion batteries are currently the technology of choice for hybrid and electric vehicles due to their decreasing cost and improved power and energy density over traditional lead-acid or nickel-metal-hydride batteries. In particular, batteries with composite electrodes have seen increased use in automotive applications due to their ability to balance energy density, power density, and cost by adjusting the amount of each material within the electrode. However, this improved performance introduces new challenges to ensure the battery pack operates safely, reliably, and durably. The vehicle's battery management system (BMS) is designed to meet these challenges, in part, by estimating the battery state of charge (SOC) and state of health (SOH). Knowledge of SOC allows the BMS to predict the available instantaneous power while ensuring the battery is operating within safe limits. As batteries age, they lose capacity and the ability to deliver power. Therefore, tracking the battery SOH is necessary to maintain accurate estimates of SOC and power throughout the battery life and give an accurate miles-to-empty metric to the driver.

Robust Adaptive Control

Robust Adaptive Control PDF Author: Petros Ioannou
Publisher: Courier Corporation
ISBN: 0486320723
Category : Technology & Engineering
Languages : en
Pages : 850

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Book Description
Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.

Neural Network-Based State-of-Charge and State-of-Health Estimation

Neural Network-Based State-of-Charge and State-of-Health Estimation PDF Author: Qi Huang
Publisher: Cambridge Scholars Publishing
ISBN: 1527552187
Category : Technology & Engineering
Languages : en
Pages : 164

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Book Description
To deal with environmental deterioration and energy crises, developing clean and sustainable energy resources has become the strategic goal of the majority of countries in the global community. Lithium-ion batteries are the modes of power and energy storage in the new energy industry, and are also the main power source of new energy vehicles. State-of-charge (SOC) and state-of-health (SOH) are important indicators to measure whether a battery management system (BMS) is safe and effective. Therefore, this book focuses on the co-estimation strategies of SOC and SOH for power lithium-ion batteries. The book describes the key technologies of lithium-ion batteries in SOC and SOH monitoring and proposes a collaborative optimization estimation strategy based on neural networks (NN), which provide technical references for the design and application of a lithium-ion battery power management system. The theoretical methods in this book will be of interest to scholars and engineers engaged in the field of battery management system research.

Modeling and State Estimation of Automotive Lithium-Ion Batteries

Modeling and State Estimation of Automotive Lithium-Ion Batteries PDF Author: Shunli Wang
Publisher: CRC Press
ISBN: 1040046754
Category : Science
Languages : en
Pages : 145

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Book Description
This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries. The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate its effectiveness in improving the accuracy of SOC and SOH estimation through theoretical and experimental analysis. The book will benefit researchers and engineers in the new energy industry and provide students of science and engineering with some innovative aspects of battery modeling.

Battery Systems Engineering

Battery Systems Engineering PDF Author: Christopher D. Rahn
Publisher: John Wiley & Sons
ISBN: 1118517059
Category : Science
Languages : en
Pages : 233

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Book Description
A complete all-in-one reference on the important interdisciplinary topic of Battery Systems Engineering Focusing on the interdisciplinary area of battery systems engineering, this book provides the background, models, solution techniques, and systems theory that are necessary for the development of advanced battery management systems. It covers the topic from the perspective of basic electrochemistry as well as systems engineering topics and provides a basis for battery modeling for system engineering of electric and hybrid electric vehicle platforms. This original approach gives a useful overview for systems engineers in chemical, mechanical, electrical, or aerospace engineering who are interested in learning more about batteries and how to use them effectively. Chemists, material scientists, and mathematical modelers can also benefit from this book by learning how their expertise affects battery management. Approaches a topic which has experienced phenomenal growth in recent years Topics covered include: Electrochemistry; Governing Equations; Discretization Methods; System Response and Battery Management Systems Include tables, illustrations, photographs, graphs, worked examples, homework problems, and references, to thoroughly illustrate key material Ideal for engineers working in the mechanical, electrical, and chemical fields as well as graduate students in these areas A valuable resource for Scientists and Engineers working in the battery or electric vehicle industries, Graduate students in mechanical engineering, electrical engineering, chemical engineering.

Battery System Modeling

Battery System Modeling PDF Author: Shunli Wang
Publisher: Elsevier
ISBN: 0323904335
Category : Science
Languages : en
Pages : 356

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Book Description
Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates. Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation Provides a dedicated chapter on active control strategies

State Estimation Strategies in Lithium-ion Battery Management Systems

State Estimation Strategies in Lithium-ion Battery Management Systems PDF Author: Shunli Wang
Publisher: Elsevier
ISBN: 0443161615
Category : Business & Economics
Languages : en
Pages : 377

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Book Description
State Estimation Strategies in Lithium-ion Battery Management Systems presents key technologies and methodologies in modeling and monitoring charge, energy, power and health of lithium-ion batteries. Sections introduce core state parameters of the lithium-ion battery, reviewing existing research and the significance of the prediction of core state parameters of the lithium-ion battery and analyzing the advantages and disadvantages of prediction methods of core state parameters. Characteristic analysis and aging characteristics are then discussed. Subsequent chapters elaborate, in detail, on modeling and parameter identification methods and advanced estimation techniques in different application scenarios. Offering a systematic approach supported by examples, process diagrams, flowcharts, algorithms, and other visual elements, this book is of interest to researchers, advanced students and scientists in energy storage, control, automation, electrical engineering, power systems, materials science and chemical engineering, as well as to engineers, R&D professionals, and other industry personnel. Introduces lithium-ion batteries, characteristics and core state parameters Examines battery equivalent modeling and provides advanced methods for battery state estimation Analyzes current technology and future opportunities

Battery Management Systems

Battery Management Systems PDF Author: Valer Pop
Publisher: Springer Science & Business Media
ISBN: 1402069456
Category : Science
Languages : en
Pages : 238

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Book Description
This book describes the field of State-of-Charge (SoC) indication for rechargeable batteries. An overview of the state-of-the-art of SoC indication methods including available market solutions from leading semiconductor companies is provided. All disciplines are covered, from electrical, chemical, mathematical and measurement engineering to understanding battery behavior. This book will therefore is for persons in engineering and involved in battery management.

Multidimensional Lithium-Ion Battery Status Monitoring

Multidimensional Lithium-Ion Battery Status Monitoring PDF Author: Shunli Wang
Publisher: CRC Press
ISBN: 1000799565
Category : Technology & Engineering
Languages : en
Pages : 355

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Book Description
Multidimensional Lithium-Ion Battery Status Monitoring focuses on equivalent circuit modeling, parameter identification, and state estimation in lithium-ion battery power applications. It explores the requirements of high-power lithium-ion batteries for new energy vehicles and systematically describes the key technologies in core state estimation based on battery equivalent modeling and parameter identification methods of lithium-ion batteries, providing a technical reference for the design and application of power lithium-ion battery management systems. Reviews Li-ion battery characteristics and applications. Covers battery equivalent modeling, including electrical circuit modeling and parameter identification theory Discusses battery state estimation methods, including state of charge estimation, state of energy prediction, state of power evaluation, state of health estimation, and cycle life estimation Introduces equivalent modeling and state estimation algorithms that can be applied to new energy measurement and control in large-scale energy storage Includes a large number of examples and case studies This book has been developed as a reference for researchers and advanced students in energy and electrical engineering.

Battery Management Systems, Volume I: Battery Modeling

Battery Management Systems, Volume I: Battery Modeling PDF Author: Gregory L. Plett
Publisher: Artech House
ISBN: 163081024X
Category : Technology & Engineering
Languages : en
Pages : 343

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Book Description
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.