Download or read book Design and Development of Advanced Machine Learning Algorithms for Lithium ion Battery State of charge Estimation written by Manjot Sidhu and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Batteries have been becoming more and more popular because of their long life and lightweight. Accurate estimation of the SOC help in making plans in an application to conserve and further enhance battery life. State of Charge (SOC) estimation is a difficult task made more challenging by changes in battery characteristics over time and their nonlinear behavior. In recent years, intelligent schemes for the estimation of the SOC have been proposed because of the absence of the formula for calculating SOC which is hard to deduce because of the effect of external factors like temperature. As the traditional methods only considered certain aspects which with the aging and degradation of the battery results in errors. To tackle this problem several methods were proposed which made use of now evolving artificial intelligence technologies. This paper presents a new SOC estimation algorithm based on kNearest neighbor and random forest regression and a comparison study is done using four algorithms Support Vector Regression, Neural Network Regression, Random Forest Regression and kNearest Neighbor. Their performance is evaluated using data from two drive cycles.

Download or read book Intelligent Lithium Ion Battery State of Charge SOC Estimation Methods written by Shunli Wang and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: To improve the accuracy and stability of power battery state of charge (SOC) estimation, this book proposes a SOC estimation method for power lithium batteries based on the fusion of deep learning and filtering algorithms. More specifically, the book proposes a SOC estimation method for Li-ion batteries using bi-directional long and short-term memory neural networks (BiLSTM), which overcomes the problem that long and short-term memory neural networks (LSTM) pose, because they can only learn in one direction, resulting in poor feature extraction and memory effect. The book provides some technical references for the design, matching, and application of power lithium-ion battery management systems, and contributes to the development of new energy technology applications.

Download or read book Advanced Model Based Charging Control for Lithium Ion Batteries written by Quan Ouyang and published by Springer Nature. This book was released on 2023-01-01 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the most state-of-the-art advanced model-based charging control technologies for lithium-ion batteries are explained from the fundamental theories to practical designs and applications, especially on the battery modelling, user-involved, and fast charging control algorithm design. Moreover, some other necessary design considerations, such as battery pack charging control with centralized and distributed structures, are also introduced to provide excellent solutions for improving the charging performance and extending the lifetime of the batteries/battery packs. Finally, some future directions are mentioned in brief. This book summarizes the model-based charging control technologies from the cell level to the battery pack level. From this book, readers interested in battery management can have a broad view of modern battery charging technologies. Readers who have no experience in battery management can learn the basic concept, analysis methods, and design principles of battery charging systems. Even for the readers who are occupied in this area, this book also provides rich knowledge on engineering applications and future trends of battery charging technologies.

Download or read book State Estimation Strategies in Lithium ion Battery Management Systems written by Shunli Wang and published by Elsevier. This book was released on 2023-07-14 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Advanced Machine Learning Technologies and Applications written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2021-03-04 with total page 1144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the 6th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2021) held in Cairo, Egypt, during March 22–24, 2021, and organized by the Scientific Research Group of Egypt (SRGE). The papers cover current research Artificial Intelligence Against COVID-19, Internet of Things Healthcare Systems, Deep Learning Technology, Sentiment analysis, Cyber-Physical System, Health Informatics, Data Mining, Power and Control Systems, Business Intelligence, Social media, Control Design, and Smart Systems.

Download or read book Neural Network Based State of Charge and State of Health Estimation written by Qi Huang and published by Cambridge Scholars Publishing. This book was released on 2023-11-16 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Battery System Modeling written by Shunli Wang and published by Elsevier. This book was released on 2021-06-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Intelligent Lithium Ion Battery State of Charge SOC Estimation Methods written by Shunli Wang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: To improve the accuracy and stability of power battery state of charge (SOC) estimation, this book proposes a SOC estimation method for power lithium batteries based on the fusion of deep learning and filtering algorithms. More specifically, the book proposes a SOC estimation method for Li-ion batteries using bi-directional long and short-term memory neural networks (BiLSTM), which overcomes the problem that long and short-term memory neural networks (LSTM) po.

Download or read book Multidimensional Lithium Ion Battery Status Monitoring written by Shunli Wang and published by CRC Press. This book was released on 2022-12-28 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Modeling and State Estimation of Automotive Lithium Ion Batteries written by Shunli Wang and published by CRC Press. This book was released on 2024-07-16 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Enhanced Battery State of Charge Estimation by Machine Learning and Unscented Kalman Filter written by Kuo-Hao Liao and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion (Li-ion) batteries have grown popular in portable communication equipment and electric vehicles these recent years by their high energy density and long cycle life compared with other batteries. State of charge (Soc) estimation is the method that provides the information to the battery management systems (BMSs) to prevent the batteries from over-charging or over-discharging. However, the State of Charge represents the battery's remaining capacity out of its total capacity, and it is not easy to measure it from physical properties. The physical properties difficulty comes from the battery's chemical reaction that requires a highly accurate device to track parameter changes inside the battery. Machine Learning algorithm is helpful to solve this circumstance. Machine Learning allows to train a model by the inputs and output data and use statistical analysis to solve the output values within a specific range. This research focuses on developing a machine learning algorithm that can calculate the State of Charge based on voltage, current, and temperature parameters. This paper achieved reasonable accuracy by using the Unscented Kalman Filter after the Support Vector Machine Learning.

Download or read book Advances in Lithium Ion Batteries for Electric Vehicles written by Haifeng Dai and published by Elsevier. This book was released on 2024-02-26 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Lithium-Ion Batteries for Electric Vehicles: Degradation Mechanism, Health Estimation, and Lifetime Prediction examines the electrochemical nature of lithium-ion batteries, including battery degradation mechanisms and how to manage the battery state of health (SOH) to meet the demand for sustainable development of electric vehicles. With extensive case studies, methods and applications, the book provides practical, step-by-step guidance on battery tests, degradation mechanisms, and modeling and management strategies. The book begins with an overview of Li-ion battery aging and battery aging tests before discussing battery degradation mechanisms and methods for analysis. Further methods are then presented for battery state of health estimation and battery lifetime prediction, providing a range of case studies and techniques. The book concludes with a thorough examination of lifetime management strategies for electric vehicles, making it an essential resource for students, researchers, and engineers needing a range of approaches to tackle battery degradation in electric vehicles. Evaluates the cause of battery degradation from the material level to the cell level Explains key battery basic lifetime test methods and strategies Presents advanced technologies of battery state of health estimation

Download or read book Advanced Approaches Applied to Materials Development and Design Predictions written by Abílio M. P. De Jesus and published by MDPI. This book was released on 2020-03-25 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thematic issue on advanced simulation tools applied to materials development and design predictions gathers selected extended papers related to power generation systems, presented at the XIX International Colloquium on Mechanical Fatigue of Metals (ICMFM XIX), organized at University of Porto, Portugal, in 2018. In this issue, the limits of the current generation of materials are explored, which are continuously being reached according to the frontier of hostile environments, whether in the aerospace, nuclear, or petrochemistry industry, or in the design of gas turbines where efficiency of energy production and transformation demands increased temperatures and pressures. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on failure mechanism modeling and simulation of materials are covered. As the Guest Editors, we would like to thank all the authors who submitted papers to this Special Issue. All the papers published were peer-reviewed by experts in the field whose comments helped to improve the quality of the edition. We also would like to thank the Editorial Board of Materials for their assistance in managing this Special Issue.

Download or read book Techno societal 2022 written by Prashant M. Pawar and published by Springer Nature. This book was released on 2023-10-24 with total page 1029 pages. Available in PDF, EPUB and Kindle. Book excerpt: “This book, divided into two volumes, originates from Techno-Societal 2022: the 4th International Conference on Advanced Technologies for Societal Applications, Maharashtra, India. The conference brings together faculty members from various engineering colleges to solve relevant regional problems in India, under the guidance of eminent researchers from various reputed organizations. The focus of Volume - I is on technologies that help develop and improve society, with particular emphasis on sensor and ICT-based technologies for the betterment of people, technologies for agriculture and healthcare, micro and nano technological applications, as well as Artificial Intelligence and Big Data. Volume - II delves into commercially successful rural and agricultural technologies, engineering for rural development, ICT-based societal applications, manufacturing and fabrication processes for societal applications, material science & composites, and sensor, image, and data-driven societal technologies. This conference aims to provide a platform for innovators to share their best practices or products developed to solve specific local problems, which in turn may inspire other researchers to solve similar problems in their regions. Additionally, technologies proposed by expert researchers may find applications in different regions, making it a multidisciplinary platform for reporting innovations at different levels in Science, Engineering, and Technology.”

Download or read book Mathematical Modeling of Lithium Batteries written by Krishnan S. Hariharan and published by Springer. This book was released on 2017-12-28 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals—often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. The authors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier. Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across—from detailed electrochemical models to algorithms used for real time estimation on a microchip—is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework—often invoking basic principles of thermodynamics or transport phenomena—and ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and health estimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well. The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models.

Download or read book Robust Battery Management System Design With MATLAB written by Balakumar Balasingam and published by Artech House. This book was released on 2023-06-30 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Battery Management Algorithm for Electric Vehicles written by Rui Xiong and published by Springer Nature. This book was released on 2019-09-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces readers to the core algorithms of battery management system (BMS) for electric vehicles. These algorithms cover most of the technical bottlenecks encountered in BMS applications, including battery system modeling, state of charge (SOC) and state of health (SOH) estimation, state of power (SOP) estimation, remaining useful life (RUL) prediction, heating at low temperature, and optimization of charging. The book not only presents these algorithms, but also discusses their background, as well as related experimental and hardware developments. The concise figures and program codes provided make the calculation process easy to follow and apply, while the results obtained are presented in a comparative way, allowing readers to intuitively grasp the characteristics of different algorithms. Given its scope, the book is intended for researchers, senior undergraduate and graduate students, as well as engineers in the fields of electric vehicles and energy storage.