Download or read book Diagnosis and Prognosis of Degradation in Lithium ion Batteries written by Christoph Birkl and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Degradation Diagnostics of Lithium ion Batteries for Automotive Applications written by Carlos Pastor-Fernández and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Lista Derer Englischen Schiffe Welche Seit dem im Jahr 1713 zu Utrecht geschlossenen Frieden von denen Spaniern in West Indien weggenommen worden written by and published by . This book was released on 1727 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Lithium Ion Batteries written by Yoshiaki Kato and published by CRC Press. This book was released on 2019-04-05 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-performance secondary batteries, also called rechargeable or storage batteries, are a key component of electric automobiles, power storage for renewable energies, load levellers of electric power lines, base stations for mobile phones, and emergency power supply in hospitals, in addition to having application in energy security and realization of a low-carbon and resilient society. A detailed understanding of the physics and chemistry that occur in secondary batteries is required for developing next-generation secondary batteries with improved performance. Among various types of secondary batteries, lithium-ion batteries are most widely used because of their high energy density, small memory effect, and low self-discharge rate. This book introduces lithium-ion batteries, with an emphasis on their overview, roadmaps, and simulations. It also provides extensive descriptions of ion beam analysis and prospects for in situ diagnostics of lithium-ion batteries. The chapters are written by specialists in cutting-edge research on lithium-ion batteries and related subjects. The book will be a great reference for advanced undergraduate- and graduate-level students, researchers, and engineers in electrochemistry, nanotechnology, and diagnostic methods and instruments.

Download or read book Design Optimization Approach to Estimate the Second Life Lithium ion Batteries Life Cycle Prediction written by Kwangwoo Yeum and published by . This book was released on 2022 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium ion (Li-ion) batteries degrade with cyclic usage and storage duration. Batteries close to their end-of-life can no longer fulfill their performance requirements, and have an increased likelihood of catastrophic failures. Different usage conditions, complex manufacturing, and lack of essential data contribute to the complex degradation of second life batteries and hinder accurate analysis of battery capacity degradation. Therefore, a quick and precise diagnosis of used batteries has become an important research area for battery management, specifically in large-scale power storage systems. This thesis illustrates potential approaches for diagnosing battery degradation, considering both a physical-based and a data-driven model. The main objective is to boost the degradation prediction with the data-driven model by leveraging artificially generated data from the physical model. The approach is divided into two steps with two different battery cell models. A gradient-free optimization approach is introduced with the most widely used battery model (21700), which comes with published data of its battery cell structure, to optimize inside-of-the-cell structure. We estimate the physical battery cell structure to acquire artificial data and compare the performance of the estimated battery against the original battery. Then the degradation prediction is investigated with the A123 battery, which has extensive and high quality of battery degradation data but lacks exact cell physical structural information. We acquire artificial degradation data by estimating the physical battery cell structure with the optimization approach, and then utilize these data to boost the original battery life cycle prediction. Linear regression and backpropagation methods (resilient backpropagation, conjugate backpropagation, and bayesian regularization backpropagation) are applied along with various test matrices and cross-validation to compare the life cycle predictions. The life cycle prediction was first conducted with only the actual data. Then the artificial data was added to the training sets to conduct the life cycle prediction. The life cycle prediction error with actual data was improved with resilient backpropagation and a sigmoid activation function by 4 - 6% compared to linear regression. Backpropagation performs better on test sets containing a large amount of extreme values than the linear regression. Lastly, the prediction results with artificial data and actual data were compared by using the regression and resilient backpropagation. Adding artificial data reduced the life cycle prediction error by 0.3 - 1.3% in the regression method; there was a greater improvement when the life cycle prediction error with actual data was over 15%. However, with the backpropagation method, adding artificial data resulted in larger prediction errors.

Download or read book Fault Diagnosis and Failure Prognostics of Lithium ion Battery Based on Least Squares Support Vector Machine and Memory Particle Filter Framework written by Mohammed Ali Lskaafi and published by . This book was released on 2015 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: A novel data driven approach is developed for fault diagnosis and remaining useful life (RUL) prognostics for lithium-ion batteries using Least Square Support Vector Machine (LS-SVM) and Memory-Particle Filter (M-PF). Unlike traditional data-driven models for capacity fault diagnosis and failure prognosis, which require multidimensional physical characteristics, the proposed algorithm uses only two variables: Energy Efficiency (EE), and Work Temperature. The aim of this novel framework is to improve the accuracy of incipient and abrupt faults diagnosis and failure prognosis. First, the LSSVM is used to generate residual signal based on capacity fade trends of the Li-ion batteries. Second, adaptive threshold model is developed based on several factors including input, output model error, disturbance, and drift parameter. The adaptive threshold is used to tackle the shortcoming of a fixed threshold. Third, the M-PF is proposed as the new method for failure prognostic to determine Remaining Useful Life (RUL). The M-PF is based on the assumption of the availability of real-time observation and historical data, where the historical failure data can be used instead of the physical failure model within the particle filter. The feasibility of the framework is validated using Li-ion battery prognostic data obtained from the National Aeronautic and Space Administration (NASA) Ames Prognostic Center of Excellence (PCoE). The experimental results show the following: (1) fewer data dimensions for the input data are required compared to traditional empirical models; (2) the proposed diagnostic approach provides an effective way of diagnosing Li-ion battery fault; (3) the proposed prognostic approach can predict the RUL of Li-ion batteries with small error, and has high prediction accuracy; and, (4) the proposed prognostic approach shows that historical failure data can be used instead of a physical failure model in the particle filter.

Download or read book A Hybrid Prognostic Approach for Battery Health Monitoring and Remaining useful life Prediction written by Mohamed Ahwiadi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion (Li-ion) batteries are commonly used in various industrial and domestic applications, such as portable communication devices, medical equipment, and electric vehicles. However, the Li-ion battery performance degrades over time due to the aging phenomenon, which may lead to system performance degradation or even safety issues, especially in vehicle and industrial applications. Reliable battery health monitoring and prognostics systems are extremely useful for improving battery performance, to diagnose the battery's state-of-health (SOH), and to predict its remaining-useful-life (RUL). In general, it is challenging to accurately track the battery's nonlinear degradation features as battery degradation parameters are almost inaccessible to measure using general sensors. In addition, a battery is an electro-chemical system whose properties vary with variations in environmental and operating conditions. Although there are some techniques proposed in the literature for battery SOH estimation and RUL analysis, these techniques have clear limitations in applications, due to reasons such as lack of proper representation of the posterior probability density functions to capture and model the nonlinear dynamic system of Li-ion batteries. In addition, these techniques cannot effectively deal with the time-varying system properties, especially for long-term predictions. To tackle these problems, a novel hybrid prognostic framework has been developed in this PhD work for battery SOH monitoring and RUL prediction. It integrates two new models: the model-based filtering method and the evolving fuzzy rule-based prediction technique. The strategy is to propose and use more efficient techniques in each module to improve processing, accuracy and reliability. Firstly, a newly enhanced mutated particle filter technique is proposed to enhance the performance of particle filter technique and improve the modeling accuracy of the battery system's degradation process. It consists of three novel aspects: an enhanced mutation approach, a selection scheme, and an outlier detection method. Secondly, an adaptive evolving fuzzy technique is suggested for long-term time series forecasting. It has a novel error-assessment method to control the fuzzy cluster/rule generation process-also, a new optimization technique to enhance incremental learning and improve modeling efficiency. Finally, a new hybrid prognostic framework integrates the merits of both proposed techniques to capture the underlying physics of the battery systems for its SOH estimation, and improve the prognosis of dynamic system for long-term prediction of Li-ion battery RUL. The effectiveness of the proposed techniques is verified through simulation tests using some commonly used-benchmark models and battery databases in this field, such as the one from the National Aeronautics and Space Administration (NASA) Ames Prognostic Center of Excellence. Test results have shown that the proposed hybrid prognostics framework can effectively capture the battery SOH degradation process, and can accurately predict its RUL.

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 2024-02-15 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 Battery Aging Diagnosis and Prognosis for Hybrid Electrical Vehicles Applications written by Mihai Spataru and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The present thesis presents an insight to the problem of battery aging diagnosis and prognosis problem for automotive applications (PHEV vehicles). The work has been carried out at Center for Automotive Research (CAR) USA. The problem itself is not a trivial one and it requiters certain systems theory tools that have been well developed in the literature to be carried out on an experimental data set that has been obtained at CAR by aging LI-ION batteries throughout various real time driving cycles profiles. Estimating the Remaining Useful Life (RUL) of a component is at the center of the problem of prognosis and health management. It is a useful tool that informs the engineer with how much time it is left before the functionality of the competent is lost. The problem of prediction is to deal with multiple sources of uncertainties such as noises in the systems, degradation in the component's functionality.

Download or read book Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems written by Hamid Reza Karimi and published by Academic Press. This book was released on 2021-06-05 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems. Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers – mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more. - Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications - Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more - Gives numerical and simulation results in each chapter to reflect engineering practices

Download or read book All Solid State Thin Film Lithium Ion Batteries written by Alexander Skundin and published by CRC Press. This book was released on 2021-09-08 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, accessible introduction to modern all-solid-state lithium-ion batteries. All-solid-state thin-film lithium-ion batteries present a special and especially important version of lithium-ion ones. They are intended for battery-powered integrated circuit cards (smart-cards), radio-frequency identifier (RFID) tags, smart watches, implantable medical devices, remote microsensors and transmitters, Internet of Things systems, and various other wireless devices including smart building control and so on. Comprising four chapters the monograph explores and provides: The fundamentals of rechargeable batteries, comparison of lithium-ion batteries with other kinds, features of thin-film batteries. A description of functional materials for all-solid-state thin-film batteries. Various methods for applying functional layers of an all-solid-state thin-film lithium-ion battery. Diagnostics of functional layers of all-solid-state thin-film lithium-ion batteries. The monograph is intended for teachers, researchers, advanced undergraduate students, and post-graduate students of profile faculties of universities, as well as for developers and manufacturers of thin-film lithium-ion batteries.

Download or read book State of health Diagnosis of Lithium ion Battery Systems and Health based Control written by Zhiyong Xia and published by . This book was released on 2021 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion batteries are widely used in battery energy storage systems (BESS) because of their unique advantages, such as high energy density. State-of-health (SOH) estimation, as a critical function of a battery management system (BMS), is important to improve the safety and reliability of lithium-ion BESS. One objective of this dissertation is to develop fast and accurate SOH estimation methods to overcome shortcomings of conventional methods, such as slow estimation speed. Another main objective of this dissertation is to develop battery health-based control algorithms that utilize the output of SOH estimators. Chapter 1 presents an introduction to BESS and BMS and a literature review. It points out the challenges and importance of developing SOH estimation methods with improved performance such as speed and battery health-based SOC balancing control algorithms. Chapter 2 discusses the development of an in-house autonomous battery ageing platform. The developed platform can age a battery autonomously while obtaining and recording experimentally measured data of interest to support battery health diagnosis investigation and research. Chapter 3 analyzes the aggregated battery ageing data collected from the developed autonomous battery ageing platform. Several distinctive SOH indicators are identified to reflect the degradation level of battery to support the development of SOH estimators. Chapter 4 focuses on the development of power electronics based real-time online complex impedance spectrum measurement methods. These developed measurement methods support the development of online impedance based SOH estimators which provide fast SOH estimation for battery cells. In chapter 5, the correlations between the identified SOH indicators presented in chapter 3 and the SOH values of battery cells are utilized to develop deep neural network (DNN) based SOH estimators. It is observed that the diversity of SOH indicators used as the input of DNN can substantially improve estimation performance. Chapter 6 presents a battery health based SOC balancing control method. The presented method allows for drawing energy from battery cells intelligently based on the SOH differences among different battery cells, which helps to improve energy utilization efficiency and reliability of BESS. Chapter 7 concludes the research work presented in this dissertation and discusses potential future research.

Download or read book Diagnostic Examination of Generation 2 Lithium ion Cells and Assessment Ofperformance Degradation Mechanisms written by J. Knuth and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Advanced Technology Development (ATD) Program is a multilaboratory effort to assist industrial developers of high-power lithium-ion batteries overcome the barriers of cost, calendar life, abuse tolerance, and low-temperature performance so that this technology may be rendered practical for use in hybrid electric vehicles (HEVs). Included in the ATD Program is a comprehensive diagnostics effort conducted by researchers at Argonne National Laboratory (ANL), Brookhaven National Laboratory (BNL), and Lawrence Berkeley National Laboratory (LBNL). The goals of this effort are to identify and characterize processes that limit lithium-ion battery performance and calendar life, and ultimately to describe the specific mechanisms that cause performance degradation. This report is a compilation of the diagnostics effort conducted since spring 2001 to characterize Generation 2 ATD cells and cell components. The report is divided into a main body and appendices. Information on the diagnostic approach, details from individual diagnostic techniques, and details on the phenomenological model used to link the diagnostic data to the loss of 18650-cell electrochemical performance are included in the appendices. The main body of the report includes an overview of the 18650-cell test data, summarizes diagnostic data and modeling information contained in the appendices, and provides an assessment of the various mechanisms that have been postulated to explain performance degradation of the 18650 cells during accelerated aging. This report is intended to serve as a ready reference on ATD Generation 2 18650-cell performance and provide information on the tools for diagnostic examination and relevance of the acquired data. A comprehensive account of our experimental procedures and resulting data may be obtained by consulting the various references listed in the text. We hope that this report will serve as a roadmap for the diagnostic analyses of other lithium-ion technologies being evaluated for HEV applications. It is our hope that the information contained in this report will lead to the development of new lithium-ion cell chemistries and designs that will meet the 15-year cell calendar-life goal established by DOE's FreedomCar and Fuel Partnership.

Download or read book The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles ICEIV 2022 written by Fengchun Sun and published by Springer Nature. This book was released on 2023-05-10 with total page 1344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022), held online, from December 3 to December 4, 2022. The topics covered include but are not limited to energy storage, power and energy systems, electrified/intelligent transportation, batteries and management, and power electronics. The papers share the latest findings in energy storage and intelligent vehicles, making the book a valuable asset for researchers, engineers, university students, etc.

Download or read book 2021 IEEE XXVIII International Conference on Electronics Electrical Engineering and Computing INTERCON written by IEEE Staff and published by . This book was released on 2021-08-05 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We invite contributions on the latest development of the applications on electronics, electrical engineering and computing

Download or read book Fault Diagnosis Prognosis and Reliability for Electrical Machines and Drives written by Elias G. Strangas and published by John Wiley & Sons. This book was released on 2021-10-26 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect failure and signals, signal processing, and analysis. The book then moves on to describe the features of these signals and the methods commonly used to extract these features to diagnose the health of a motor or drive, as well as the methods used to identify the state of health and differentiate between possible faults or their severity. Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives discusses the tools used to recognize trends towards failure and the estimation of remaining useful life. It addresses the relationships between fault diagnosis, failure prognosis, and fault mitigation. The book also provides: A thorough introduction to the modes of failure, how early failure precursors manifest themselves in signals, and how features extracted from these signals are processed A comprehensive exploration of the fault diagnosis, the results of characterization, and how they used to predict the time of failure and the confidence interval associated with it A focus on medium-sized drives, including induction, permanent magnet AC, reluctance, and new machine and drive types Perfect for researchers and students who wish to study or practice in the rea of electrical machines and drives, Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives is also an indispensable resource for researchers with a background in signal processing or statistics.

Download or read book Fault Detection Diagnosis and Prognosis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2020-02-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.