State Estimation Strategies In Lithium Ion Battery Management Systems
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State Estimation Strategies In Lithium Ion Battery Management Systems
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Author : Shunli Wang
language : en
Publisher: Elsevier
Release Date : 2023-07-14
State Estimation Strategies In Lithium Ion Battery Management Systems written by Shunli Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-14 with Business & Economics categories.
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
Multidimensional Lithium Ion Battery Status Monitoring
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Author : Shunli Wang
language : en
Publisher: Emerging Materials and Technologies
Release Date : 2022-12-28
Multidimensional Lithium Ion Battery Status Monitoring written by Shunli Wang and has been published by Emerging Materials and Technologies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-28 with Electric automobiles categories.
This book focuses on equivalent circuit modeling, parameter identification, and state estimation in Li-ion battery power applications.
Modeling And State Estimation Of Automotive Lithium Ion Batteries
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Author : Fan Wu
language : en
Publisher:
Release Date : 2024
Modeling And State Estimation Of Automotive Lithium Ion Batteries written by Fan Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Science categories.
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.
Neural Network Based State Of Charge And State Of Health Estimation
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Author : Qi Huang
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2023-11-16
Neural Network Based State Of Charge And State Of Health Estimation written by Qi Huang and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-16 with Technology & Engineering categories.
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.
Long Term Health State Estimation Of Energy Storage Lithium Ion Battery Packs
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Author : Qi Huang
language : en
Publisher: Springer Nature
Release Date : 2023-08-18
Long Term Health State Estimation Of Energy Storage Lithium Ion Battery Packs written by Qi Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-18 with Technology & Engineering categories.
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.
State Estimation Performance Prediction And Health Assessment Of Lithium Ion Batteries For Advanced Battery Management Systems
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Author :
language : en
Publisher:
Release Date : 2014
State Estimation Performance Prediction And Health Assessment Of Lithium Ion Batteries For Advanced Battery Management Systems written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Lithium ion batteries categories.
Advanced Battery Management Technologies For Electric Vehicles
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Author : Rui Xiong
language : en
Publisher: Wiley
Release Date : 2018-12-21
Advanced Battery Management Technologies For Electric Vehicles written by Rui Xiong and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-21 with Electric vehicles categories.
ADVANCED BATTERY MANAGEMENT TECHNOLOGIES FOR ELECTRIC VEHICLES A comprehensive examination of advanced battery management technologies and practices in modern electric vehicles Policies surrounding energy sustainability and environmental impact have become of increasing interest to governments, industries, and the general public worldwide. Policies embracing strategies that reduce fossil fuel dependency and greenhouse gas emissions have driven the widespread adoption of electric vehicles (EVs), including hybrid electric vehicles (HEVs), pure electric vehicles (PEVs) and plug-in hybrid electric vehicles (PHEVs). Battery management systems (BMSs) are crucial components of such vehicles, protecting a battery system from operating outside its Safe Operating Area (SOA), monitoring its working conditions, calculating and reporting its states, and charging and balancing the battery system. Advanced Battery Management Technologies for Electric Vehicles is a compilation of contemporary model-based state estimation methods and battery charging and balancing techniques, providing readers with practical knowledge of both fundamental concepts and practical applications. This timely and highly-relevant text covers essential areas such as battery modeling and battery state of charge, energy, health and power estimation methods. Clear and accurate background information, relevant case studies, chapter summaries, and reference citations help readers to fully comprehend each topic in a practical context. Key features: Offers up-to-date coverage of modern battery management technology and practice Provides case studies of real-world engineering applications Guides readers from electric vehicle fundamentals to advanced battery management topics Includes chapter introductions and summaries, case studies, color charts, graphs, and illustrations Suitable for advanced undergraduate and graduate coursework, Advanced Battery Management Technologies for Electric Vehicles is equally valuable as a reference for professional researchers and engineers.
Intelligent Lithium Ion Battery State Of Charge Soc Estimation Methods
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Author : Shunli Wang
language : en
Publisher:
Release Date : 2024
Intelligent Lithium Ion Battery State Of Charge Soc Estimation Methods written by Shunli Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
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.
Artificial Intelligence Based State Of Health Estimation Of Lithium Ion Batteries
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Author : Remus Teodorescu
language : en
Publisher:
Release Date : 2024-02-27
Artificial Intelligence Based State Of Health Estimation Of Lithium Ion Batteries written by Remus Teodorescu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Science categories.
This reprint aims to showcase manuscripts presenting efficient SOH estimation methods using AI which exhibit good performance such as high accuracy, high robustness against the changes in working conditions, and good generalization, etc. Lithium-ion batteries have a wide range of applications, but one of their biggest problems is their limited lifetime due to performance degradation during usage. It is, therefore, essential to determine the battery's state of health (SOH) so that the battery management system can control the battery, enabling it to run in the best state and thus prolonging its lifetime. Artificial intelligence (AI) technologies possess immense potential in inferring battery SOH and can extract aging information (i.e., SOH features) from measurements and relate them to battery performance parameters, avoiding a complex battery modeling process.
Fuzzy Filter Based State Of Energy Estimation For Lithium Ion Batteries
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Author : Shunli Wang
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2024-03-21
Fuzzy Filter Based State Of Energy Estimation For Lithium Ion Batteries written by Shunli Wang and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-21 with Technology & Engineering categories.
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.