Download or read book Electrochemical Model Based Condition Monitoring of a Li ion Battery Using Fuzzy Logic written by Vinay Kumar Shimoga Muddappa and published by . This book was released on 2014 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a strong urge for advanced diagnosis method, especially in high power battery packs and high energy density cell design applications, such as electric vehicle (EV) and hybrid electric vehicle segment, due to safety concerns. Accurate and robust diagnosis methods are required in order to optimize battery charge utilization and improve EV range. Battery faults cause significant model parameter variation affecting battery internal states and output. This work is focused on developing diagnosis method to reliably detect various faults inside lithium-ion cell using electrochemical model based observer and fuzzy logic algorithm, which is implementable in real-time. The internal states and outputs from battery plant model were compared against those from the electrochemical model based observer to generate the residuals. These residuals and states were further used in a fuzzy logic based residual evaluation algorithm in order to detect the battery faults. Simulation results show that the proposed methodology is able to detect various fault types including overcharge, over-discharge and aged battery quickly and reliably, thus providing an effective and accurate way of diagnosing li-ion battery faults.

Download or read book Model Based and Intelligent Monitoring and Control of Lithium ion Batteries written by Mohammad Foad Samadi and published by . This book was released on 2016 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increased concerns over the limited sources of energy and environmental impact of the petroleum-based transportation infrastructure have led to increasing interest in an electric transportation infrastructure. Thus, electrical vehicles (including electric vehicle (EV), hybrid electric vehicle (HEV), and plug-in hybrid electric vehicle (PHEV)) and related issues have gained a great deal of attention. Battery technology and battery management is a key component in this regard and has indeed remained as a central challenge in vehicle electrification. This thesis deals with monitoring and control of Lithium ion batteries. The objective is to provide novel solutions to some of the challenging issues from a control theoretic perspective. The research stream in this thesis is headed towards three general directions, i.e. monitoring, diagnostics, and control. The proposed monitoring approaches are introduced as model-based and data-based approaches. The main objective in model-based approaches is to employ the high-fidelity physics-based models of the battery for monitoring. In this thesis, two particle-filtering methods are proposed for state, and joint state and parameter estimation of such models. The data based approaches try to come up with new ideas to monitor the battery accurately but with minimum computational load. In this regard, two different approaches are considered. A Takagi-Sugeno fuzzy model is developed for Li-ion battery where by the virtue of multiple-model structure of T-S model, the non-linearities of battery dynamics and corresponding parameters can appropriately be accounted for, while keeping the local models linear and easy-to-implement control/estimation algorithms. As a completely different alternative, the "Dynamic Resistance" concept is introduced that is sensitive to the battery state of charge and aging. This parameter considers changes in states of active materials in the cell during charge and discharge as well as overall interface resistances that may develop during cell aging. It can bring a new dimension to battery monitoring by providing a new easy-to-monitor parameter where the aging of the battery is also taken into account. This parameter is modeled versus the state of charge and total power throughput of the battery using a Group Method of Data Handling (GMDH) neural network and the model is used to monitor the state of charge and state of health of the battery. A reliable fault diagnosis system for batteries can play an important role in enhanced performance and reliability of electric-based transportation. In this thesis, the physics of the problem is rather comprehensively reviewed, and some of the proposed models for failure mechanism are presented and some fault-detection algorithms for some common failure mechanism are developed. Finally, over-charge/discharge of the cells within a battery pack can affect the battery's health significantly, and would pose serious safety concerns as well. Thus, a cell balancing circuit is usually employed in battery packs in order to keep all the cells in balance. In this thesis, the control problem of a cell-balancing circuit, which is essentially a switched hybrid system, is addressed in a model-based framework by proposing a nonlinear model predictive control (NMPC) strategy.

Download or read book Optimization for Control Observation and Safety written by Guillermo Valencia-Palomo and published by MDPI. This book was released on 2020-04-01 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical optimization is the selection of the best element in a set with respect to a given criterion. Optimization has become one of the most used tools in control theory to compute control laws, adjust parameters (tuning), estimate states, fit model parameters, find conditions in order to fulfill a given closed-loop property, among others. Optimization also plays an important role in the design of fault detection and isolation systems to prevent safety hazards and production losses that require the detection and identification of faults, as early as possible to minimize their impacts by implementing real-time fault detection and fault-tolerant systems. Recently, it has been proven that many optimization problems with convex objective functions and linear matrix inequality (LMI) constraints can be solved easily and efficiently using existing software, which increases the flexibility and applicability of the control algorithms. Therefore, real-world control systems need to comply with several conditions and constraints that have to be taken into account in the problem formulation, which represents a challenge in the application of the optimization algorithms. This book offers an overview of the state-of-the-art of the most advanced optimization techniques and their applications in control engineering.

Download or read book Handbook of Power Electronics in Autonomous and Electric Vehicles written by Muhammad H. Rashid and published by Elsevier. This book was released on 2024-07-22 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Power Electronics in Autonomous and Electric Vehicles provides advanced knowledge on autonomous systems, electric propulsion in electric vehicles, radars and sensors for autonomous systems, and relevant aspects of energy storage and battery charging. The work is designed to provide clear technical presentation with a focus on commercial viability. It supports any and all aspects of a project requiring specialist design, analysis, installation, commissioning and maintenance services. With this book in hand, engineers will be able to execute design, analysis and evaluation of assigned projects using sound engineering principles and commercial requirements, policies, and product and program requirements. - Presents core power systems and engineering applications relevant to autonomous and electric vehicles in characteristic depth and technical presentation - Offers practical support and guidance with detailed examples and applications for laboratory vehicular test plans and automotive field experimentation - Includes modern technical coverage of emergent fields, including sensors and radars, battery charging and monitoring, and vehicle cybersecurity

Download or read book Fuzzy Filter Based State of Energy Estimation for Lithium Ion Batteries written by Shunli Wang and published by Cambridge Scholars Publishing. This book was released on 2024-03-21 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Awareness of the safety issues of lithium-ion batteries is crucial in the development of new energy technologies, and real-time and high-precision State of Energy (SOE) estimation is not only a prerequisite for battery safety, but also serves as the basis for predicting the remaining driving range of electric vehicles and aircrafts. In order to achieve real-time and accurate estimation of the energy state of lithium-ion batteries, this book improves the calculation method of the open-circuit voltage in the traditional second-order RC equivalent circuit model. It also combines a fuzzy controller and a dual-weighted multi-innovation algorithm to optimize the traditional Centralized Kalman Filter (CKF) algorithm in terms of the aspects of convergence speed, estimation accuracy, and algorithm robustness. This enables the precise estimation of SOE and the maximum available energy. The content of this book provides theoretical support for the development of new energy initiatives.

Download or read book Model Based Condition Monitoring and Power Management for Rechargeable Electrochemical Batteries written by Taesic Kim and published by . This book was released on 2015 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: First, this research developed high-fidelity battery models for online condition monitoring and power management of battery cells. The battery models were capable of capturing the dynamic circuit characteristics, nonlinear capacity and nonlinear open-circuit voltage effects, hysteresis effect, and temperature effect of the battery cells.

Download or read book Smart Battery Management for Enhanced Safety written by Zhongbao Wei and published by Springer Nature. This book was released on with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 Long Term Health State Estimation of Energy Storage Lithium Ion Battery Packs written by Qi Huang and published by Springer Nature. This book was released on 2023-08-18 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.

Download or read book Integrated Systems Innovations and Applications written by Madjid Fathi and published by Springer. This book was released on 2015-03-27 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the results of discussions and presentation from the latest ISDT event (2014) which was dedicated to the 94th birthday anniversary of Prof. Lotfi A. Zade, father of Fuzzy logic. The book consists of three main chapters, namely: Chapter 1: Integrated Systems Design Chapter 2: Knowledge, Competence and Business Process Management Chapter 3: Integrated Systems Technologies Each article presents novel and scientific research results with respect to the target goal of improving our common understanding of KT integration.

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 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 Intelligent Computing and Optimization written by Pandian Vasant and published by Springer Nature. This book was released on 2021-02-07 with total page 1332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Third edition of International Conference on Intelligent Computing and Optimization and as a premium fruit, this book, pursue to gather research leaders, experts and scientists on Intelligent Computing and Optimization to share knowledge, experience and current research achievements. Conference and book provide a unique opportunity for the global community to interact and share novel research results, explorations and innovations among colleagues and friends. This book is published by SPRINGER, Advances in Intelligent Systems and Computing. Ca. 100 authors submitted full papers to ICO’2020. That global representation demonstrates the growing interest of the research community here. The book covers innovative and creative research on sustainability, smart cities, meta-heuristics optimization, cyber-security, block chain, big data analytics, IoTs, renewable energy, artificial intelligence, Industry 4.0, modeling and simulation. We editors thank all authors and reviewers for their important service. Best high-quality papers have been selected by the International PC for our premium series with SPRINGER.

Download or read book Encyclopedia of Electrochemical Power Sources written by Jürgen Garche and published by Newnes. This book was released on 2013-05-20 with total page 4532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Electrochemical Power Sources is a truly interdisciplinary reference for those working with batteries, fuel cells, electrolyzers, supercapacitors, and photo-electrochemical cells. With a focus on the environmental and economic impact of electrochemical power sources, this five-volume work consolidates coverage of the field and serves as an entry point to the literature for professionals and students alike. Covers the main types of power sources, including their operating principles, systems, materials, and applications Serves as a primary source of information for electrochemists, materials scientists, energy technologists, and engineers Incorporates nearly 350 articles, with timely coverage of such topics as environmental and sustainability considerations

Download or read book Electrochemical Model Based Fault Diagnosis of Lithium Ion Battery written by Md Ashiqur Rahman and published by . This book was released on 2015 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gradient free function optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized in parameter identification of the electrochemical model of a Lithium-Ion battery having a LiCoO2 chemistry. Battery electrochemical model parameters are subject to change under severe or abusive operating conditions resulting in, for example, Navy over-discharged battery, 24-hr over-discharged battery, and over-charged battery. It is important for a battery management system to have these parameters changes fully captured in a bank of battery models that can be used to monitor battery conditions in real time. In this work, PSO methodology has been used to identify four electrochemical model parameters that exhibit significant variations under severe operating conditions. The identified battery models were validated by comparing the model output voltage with the experimental output voltage for the stated operating conditions. These identified conditions of the battery were then used to monitor condition of the battery that can aid the battery management system (BMS) in improving overall performance. An adaptive estimation technique, namely multiple model adaptive estimation (MMAE) method, was implemented for this purpose. In this estimation algorithm, all the identified models were simulated for a battery current input profile extracted from the hybrid pulse power characterization (HPPC) cycle simulation of a hybrid electric vehicle (HEV). A partial differential algebraic equation (PDAE) observer was utilized to obtain the estimated voltage, which was used to generate the residuals. Analysis of these residuals through MMAE provided the probability of matching the current battery operating condition to that of one of the identified models. Simulation results show that the proposed model based method offered an accurate and effective fault diagnosis of the battery conditions. This type of fault diagnosis, which is based on the models capturing true physics of the battery electrochemistry, can lead to a more accurate and robust battery fault diagnosis and help BMS take appropriate steps to prevent battery operation in any of the stated severe or abusive conditions.

Download or read book International Journal of Prognostics and Health Management Volume 3 color written by PHM Society and published by Lulu.com. This book was released on 2013-09-24 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: PHM Society established International Journal of Prognostics and Health Management (IJPHM) in 2009 to facilitate archival publication of peer-reviewed results from research and development in the area of PHM. As a journal solely dedicated to the emerging field of PHM IJPHM is the first of its kind and has been a focal point for dissemination of peer-reviewed PHM knowledge. While for the first few years the journal maintained only an online presence, the printed volumes will now be available and can be obtained upon request.

Download or read book Fault Diagnosis of Lithium Ion Battery Using Multiple Model Adaptive Estimation written by Amardeep Singh Sidhu and published by . This book was released on 2013 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium ion (Li-ion) batteries have become integral parts of our lives; they are widely used in applications like handheld consumer products, automotive systems, and power tools among others. To extract maximum output from a Li-ion battery under optimal conditions it is imperative to have access to the state of the battery under every operating condition. Faults occurring in the battery when left unchecked can lead to irreversible, and under extreme conditions, catastrophic damage. In this thesis, an adaptive fault diagnosis technique is developed for Li-ion batteries. For the purpose of fault diagnosis the battery is modeled by using lumped electrical elements under the equivalent circuit paradigm. The model takes into account much of the electro-chemical phenomenon while keeping the computational effort at the minimum. The diagnosis process consists of multiple models representing the various conditions of the battery. A bank of observers is used to estimate the output of each model; the estimated output is compared with the measurement for generating residual signals. These residuals are then used in the multiple model adaptive estimation (MMAE) technique for generating probabilities and for detecting the signature faults. The effectiveness of the fault detection and identification process is also dependent on the model uncertainties caused by the battery modeling process. The diagnosis performance is compared for both the linear and nonlinear battery models. The non-linear battery model better captures the actual system dynamics and results in considerable improvement and hence robust battery fault diagnosis in real time. Furthermore, it is shown that the non-linear battery model enables precise battery condition monitoring in different degrees of over-discharge.